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Part II - Methods in child development research

Published online by Cambridge University Press:  26 October 2017

Brian Hopkins
Affiliation:
Lancaster University
Elena Geangu
Affiliation:
Lancaster University
Sally Linkenauger
Affiliation:
Lancaster University
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Print publication year: 2017

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References

Further reading

De Ste Croix, M., & Korff, T. (Eds.) (2012). Paediatric biomechanics and motor control: Theory and application. New York, NY: Routledge.Google Scholar
Jensen, J.L. (2005). The puzzles of motor development: How the study of developmental biomechanics contributes to the puzzle solutions. Infant and Child Development, 14, 501511.Google Scholar
Mündermann, L., Corazza, S., & Andriacchi, T.P. (2006). The evolution of methods for the capture of human movement leading to markerless motion capture for biomechanical applications. Journal of NeuroEngineering and Rehabilitation, 3, 111.Google Scholar
Nowlan, N. (2015). Biomechanics of foetal movement. European Cells & Materials, 29, 121.CrossRefGoogle ScholarPubMed

References

Bernstein, N. (1967). The coordination and regulation of movements. Oxford, UK: Pergamon Press.Google Scholar
Datar, A., & Jacknowitz, A. (2009). Birth weight effects on children’s mental, motor, and physical development: Evidence from twins data. Maternal and Child Health Journal, 13, 780794.CrossRefGoogle ScholarPubMed
Deffeyes, J.E., Harbourne, R.T., Stuberg, W.A., & Stergiou, N. (2011). Approximate entropy used to assess sitting postural sway of infants with developmental delay. Infant Behavior and Development, 34, 8199.CrossRefGoogle ScholarPubMed
Heazell, A.P., & Frøen, J.F. (2008). Methods of fetal movement counting and the detection of fetal compromise. Journal of Obstetrics and Gynaecology, 28, 147154.CrossRefGoogle ScholarPubMed
Jensen, J.L., & Bothner, K.E. (1998). Revisiting infant motor development schedules: The biomechanics of change. In Van Praagh, E. (Ed.), Pediatric anaerobic performance (pp. 2343). Champaign, IL: Human Kinetics.Google Scholar
Jensen, J.L., Schneider, K., Ulrich, B.D., Zernicke, R.F., & Thelen, E. (1994). Adaptive dynamics of the leg movement patterns of human infants: I. The effects of posture on spontaneous kicking. Journal of Motor Behavior, 26, 303312.Google Scholar
Konczak, J., Borutta, M., Topka, H., & Dichgans, J. (1995). Development of goal-directed reaching in infants: Hand trajectory formation and joint force control. Experimental Brain Research, 106, 156168.CrossRefGoogle Scholar
Kurjak, A., Andonotopo, W., Hafner, T., Salihagic Kadic, A., Stanojevic, M., Azumendi, G., & Troyano, J.M. (2006). Normal standards for fetal neurobehavioral developments: Longitudinal quantification by four-dimensional sonography. Journal of Perinatal Medicine, 34, 5665.CrossRefGoogle ScholarPubMed
Kurjak, A., Tikvica, A., Stanojevic, M., Miskovic, B., Ahmed, B., Azumendi, G., & Renzo, G.C.D. (2008). The assessment of fetal neurobehavior by three-dimensional and four-dimensional ultrasound. Journal of Maternal–Fetal & Neonatal Medicine, 21, 675684.CrossRefGoogle ScholarPubMed
McDowell, M.A., Fryar, C.D., Ogden, C.L., & Flegal, K.M. (2008). Anthropometric reference data for children and adults: United States, 2003–2006. National Health Statistics Reports; no. 10. Hyattsville, MD: National Center for Health Statistics.Google Scholar
Moh, W., Graham, J.M., Wadhawan, I., & Sanchez-Lara, P.A. (2012). Extrinsic factors influencing fetal deformations and intrauterine growth restriction. Journal of Pregnancy, 2012, 111.CrossRefGoogle ScholarPubMed
Muybridge, E. (1899). Animals in motion. London, UK: William Clowes & Sons.Google Scholar
Pitcher, J.B., Schneider, L.A., Drysdale, J.L., Ridding, M.C., & Owens, J.A. (2011). Motor system development of the preterm and low birthweight infant. Clinics in Perinatology, 38, 605625.Google Scholar
Sargent, B., Scholz, J., Reimann, H., Kubo, M., & Fetters, L. (2015). Development of infant leg coordination: Exploiting passive torques. Infant Behavior and Development, 40, 108121.Google Scholar
Schneider, K., Zernicke, R.F., Ulrich, B.D., Jensen, J.L., & Thelen, E. (1990). Understanding movement control in infants through the analysis of limb intersegmental dynamics. Journal of Motor Behavior, 22, 493520.Google Scholar
Slining, M., Adair, L.S., Goldman, B.D., Borja, J.B., & Bentley, M. (2010). Infant overweight is associated with delayed motor development. Journal of Pediatrics, 157, 2025.CrossRefGoogle ScholarPubMed
Thelen, E., Fisher, D.M., & Ridley-Johnson, R. (1984). The relationship between physical growth and a newborn reflex. Infant Behavior and Development, 7, 479493.Google Scholar
Ulrich, B.D., Schneider, K., Jensen, J.L., Zernicke, R.F., & Thelen, E. (1994). Adaptive dynamics of the leg movement patterns of human infants: II. Treadmill stepping in infants and adults. Journal of Motor Behavior, 26, 313324.Google Scholar
Zoia, S., Blason, L., D’Ottavio, G., Bulgheroni, M., Pezzetta, E., Scabar, A., & Castiello, U. (2006). Evidence of early development of action planning in the human foetus: A kinematic study. Experimental Brain Research, 176, 217226.Google Scholar
Zoia, S., Blason, L., D’Ottavio, G., Biancotto, M., Bulgheroni, M., & Castiello, U. (2013). The development of upper limb movements: From fetal to post-natal life. PLoS ONE, 8, 19.Google Scholar

Further reading

Abubakar, A., Van de Vijver, F.J.R., Mithwani, S., Obiero, E., Lewa, N., Katana, K., Crawley, J., & Holding, P. (2007). Assessing developmental outcomes in Kenyan children following prophylaxis for seizures in cerebral malaria. Journal of Health Psychology, 12, 417430.Google Scholar
Berry, J.W., Poortinga, Y.H., Breugelmans, S.M., Chasiotis, A., & Sam, D. (2011). Cross-cultural psychology: Theory and applications. Cambridge, UK: Cambridge University Press.Google Scholar
Chasiotis, A., Bender, M., & Hofer, J. (2014). Childhood context explains cultural variance in implicit parenting motivation: Results from two studies with six samples from Cameroon, Costa Rica, Germany, and PR China. Evolutionary Psychology, 2, 295317.Google Scholar
Matsumoto, D., & Van de Vijver, F.J.R. (Eds.) (2011). Cross-cultural research methods in psychology. Cambridge, UK: Cambridge University Press.Google Scholar
Senese, V.P., Bornstein, M.H., Haynes, O.M., Rossi, G., & Venuti, P. (2012). A cross-cultural comparison of mothers’ beliefs about their parenting very young children. Infant Behavior and Development, 35, 479–88.Google Scholar

References

Arikan, S., Van de Vijver, F.J.R., & Yagmur, K. (in review). PISA mathematics and reading performance differences of mainstream European and Turkish immigrant students.Google Scholar
Campbell, D.T. (1986). Science’s social system of validity-enhancing collective belief change and the problems of the social sciences. In Fiske, D.W. & Shweder, R.A. (Eds.), Metatheory in social science: Pluralities and subjectivities (pp. 108135). Chicago, IL: University of Chicago Press.Google Scholar
Cattell, R.B. (1940). A culture-free intelligence test. Journal of Educational Psychology, 31, 176199.Google Scholar
Cheung, F.M. (2012). Mainstreaming culture in psychology. American Psychologist, 67, 721730.Google Scholar
Dasen, P.R. (1972). Cross-cultural Piagetian research: Summary. Journal of Cross-Cultural Psychology, 3, 2339.CrossRefGoogle Scholar
Fontaine, J. (2005). Equivalence. Encyclopedia of Social Measurement, 1, 803813.Google Scholar
He, J., & Van de Vijver, F.J.R. (2015). The value of keeping an open eye for methodological issues in research on resilience and culture. In Theron, L.C., Liebenberg, L., & Ungar, M. (Eds.), Youth resilience and culture: Commonalities and complexities (pp. 189201). New York, NY: Springer.CrossRefGoogle Scholar
Kağitcibaşi, C. (2007). Family, self, and human development across countries: Theory and applications (2nd ed.). Mahwah, NJ: Erlbaum.Google Scholar
Keller, H. (2007). Cultures of infancy. Mahwah, NJ: Erlbaum.Google Scholar
Matsumoto, D., & Van de Vijver, F.J.R. (Eds.) (2011). Cross-cultural research methods in psychology. Cambridge, UK: Cambridge University Press.Google Scholar
Regnault, A., & Herdman, M. (2015). Using quantitative methods within the universalist model framework to explore the cross-cultural equivalence of patient-reported outcome instruments. Quality of Life Research, 24, 115–124.CrossRefGoogle ScholarPubMed
Rindermann, H. (2007). The g‐factor of international cognitive ability comparisons: The homogeneity of results in PISA, TIMSS, PIRLS and IQ‐tests across nations. European Journal of Personality, 21, 667706.Google Scholar
Serpell, R. (1993). The significance of schooling: Life-journeys in an African society. Cambridge, UK: Cambridge University Press.Google Scholar
Tronick, E.Z., Morelli, G.A., & Winn, S. (1987). Multiple caretaking of Efe (Pygmy) infants. American Anthropologist, 89, 96106.CrossRefGoogle Scholar
Tronick, E.Z., Morelli, G.A., & Ivey, P.K. (1992). The Efe forager infant and toddler’s pattern of social relationships: Multiple and simultaneous. Developmental Psychology, 28, 568577.Google Scholar
Van de Vijver, F.J.R., & Poortinga, Y.H. (1997). Towards an integrated analysis of bias in cross-cultural assessment. European Journal of Psychological Assessment, 13, 2937.CrossRefGoogle Scholar
Van de Vijver, F.J.R., & Tanzer, N. (1997). Bias and equivalence in cross-cultural assessment. European Review of Applied Psychology, 47, 263279.Google Scholar
Wober, M. (1969). Distinguishing centri-cultural from cross-cultural tests and research. Perceptual and Motor Skills, 28, 488.CrossRefGoogle Scholar

Further reading

Parker, S.T., & McKinney, M.L. (1999). The evolution of cognitive development in monkeys, apes, and humans. Baltimore, MD: Johns Hopkins University Press.Google Scholar
Pelligrini, A.D. (2009). The role of play in human development. New York, NY: Oxford University Press.Google Scholar
Pellis, S.M., & Pellis, V.C. (2009). The playful brain: Venturing to the limits of neuroscience. Oxford, UK: Oneworld Publications.Google Scholar

References

Baarendse, P.J.J., Counotte, D.S., O’Donnell, P., & Vanderschuren, L.J.M.J. (2013). Early social experience is critical for the development of cognitive control and dopamine modulation of prefrontal cortex function. Neuropsychopharmacology, 38, 14851494.CrossRefGoogle ScholarPubMed
Bell, H.C., Pellis, S.M., & Kolb, B. (2010). Juvenile peer play experience and the development of the orbitofrontal and medial prefrontal cortices. Behavioural Brain Research, 207, 713.CrossRefGoogle ScholarPubMed
Diamond, A., Barnett, W.S., Thomas, J., & Munro, S. (2007). Preschool program improves cognitive control. Science, 318, 13871388.Google Scholar
Einon, D.F., Morgan, M.J., & Kibbler, C.C. (1978). Brief periods of socialization and later behavior in the rat. Developmental Psychobiology, 11, 213225.Google Scholar
Himmler, B.T., Pellis, S.M., & Kolb, B. (2013). Juvenile play experience primes neurons in the medial prefrontal cortex. Neuroscience Letters, 556, 4245.CrossRefGoogle ScholarPubMed
Himmler, B.T., Stryjek, R., Modlińska, K., Derksen, S.M., Pisula, W., & Pellis, S.M. (2013). How domestication modulates play behavior: A comparative analysis between wild rats and a laboratory strain of Rattus norvegicus. Journal of Comparative Psychology, 127, 453464.CrossRefGoogle Scholar
Nunn, C.L. (2011). The comparative approach in evolutionary anthropology and biology. Chicago, IL: University of Chicago Press.Google Scholar
Parker, S.T. (1996). Using cladistics analysis of comparative data to reconstruct the evolution of cognitive development in hominids. In Martins, E. (Ed.), Phylogenies and the comparative method in animal behavior (pp. 361398). New York, NY: Oxford University Press.Google Scholar
Pellegrini, A.D. (1995). Boys’ rough-and-tumble play and social competence: Contemporaneous and longitudinal relations. In Pellegrini, A.D. (Ed.), The future of play theory: A multidisciplinary inquiry into the contributions of Brian Sutton-Smith (pp. 107126). Albany, NY: State University of New York Press.Google Scholar
Pellis, S.M., & Pellis, V.C. (1987). Play-fighting differs from serious fighting in both target of attack and tactics of fighting in the laboratory rat Rattus norvegicus. Aggressive Behavior, 13, 227242.Google Scholar
Pellis, S.M., & Pellis, V.C. (1998). Play fighting of rats in comparative perspective: A schema for neurobehavioral analyses. Neuroscience & Biobehavioral Reviews, 23, 87101.Google Scholar
van den Berg, C.L., Hol, T., Van Ree, J. M., Spruijt, B. M., Everts, H., & Koolhaas, J. M. (1999). Play is indispensable for the adequate development of coping with social challenges in the rat. Developmental Psychobiology, 34, 129–138.Google Scholar
Vanderschuren, L.J.M.J., & Trezza, V. (2014). What the laboratory rat has taught us about social play behavior: Role in behavioral development and neural mechanisms. Current Topics in Behavioral Neuroscience, 16, 189212.Google Scholar
Whishaw, I.Q., Metz, G.A.S., Kolb, B., & Pellis, S.M. (2001). Accelerated nervous system development contributes to behavioral efficiency in the laboratory mouse: A behavioral review and theoretical proposal. Developmental Psychobiology, 39, 151170.Google Scholar

Further reading

Aylward, G.P. (2005). Neurodevelopmental outcomes of infants born prematurely. Journal of Developmental and Behavioral Pediatrics, 26, 427440. Republished in 2014 as a Classic review article, Journal of Developmental and Behavioral Pediatrics, 35, 394–407.Google Scholar
Aylward, G.P. (2010). Bayley Infant Neurodevelopmental Screener: Different test, different purpose. In Weiss, L.G., Oakland, T., & Aylward, G.P. (Eds.), Bayley II. Clinical use and interpretation (pp. 201231). St. Louis, MO: Elsevier.Google Scholar
Aylward, G.P. (2011). Neuropsychological assessment of newborns, infants and toddlers. In Davis, A. (Ed.), Handbook of pediatric neuropsychology (pp. 201212). New York, NY: Springer.Google Scholar
Marks, K., Glascoe, F.P., Aylward, G.P., Shevell, M.I., Lipkin, P.H., & Squires, J.K. (2008). The thorny nature of predictive validity studies on screening tests for developmental- behavioral problems. Pediatrics, 122, 866868.Google Scholar

References

Accardo, P.J., Accardo, J.A., & Capute, A.J. (2008). A neurodevelopmental perspective on the continuum of developmental disabilities. In Accardo, P.J. (Ed.), Capute and Accardo’s neurodevelopmental disabilities in infancy and childhood (3rd ed., pp. 325). Baltimore, MD: Paul H. Brookes Publishing.Google Scholar
American Academy of Pediatrics (2006). Identifying infants and children with developmental disorders in the medical home: An algorithm for developmental surveillance and screening. Pediatrics, 118, 405420.Google Scholar
Aylward, G.P. (1997). Infant and early childhood neuropsychology. New York, NY: Plenum Press.Google Scholar
Aylward, G.P. (2009). Developmental screening and assessment: What are we thinking? Journal of Developmental and Behavioral Pediatrics, 30, 169173.Google Scholar
Aylward, G.P. (2013). Continuing issues with the Bayley-III: Where to go from here. Journal of Developmental and Behavioral Pediatrics, 34, 697701.CrossRefGoogle Scholar
Aylward, G.P., & Aylward, B.S. (2011). The changing yardstick in measurement of cognitive abilities in infancy. Journal of Developmental and Behavioral Pediatrics, 32, 465468.Google Scholar
Bagnato, S.J., Neisworth, J.T., & Pretti-Frontczak, K. (2010). LINKing authentic assessment & early childhood intervention: Best measures for best practices (2nd ed.). Baltimore, MD: Paul H. Brookes Publishing.Google Scholar
Bayley, N. (1969). Bayley scales of infant development. New York, NY: The Psychological Corporation.Google Scholar
Bayley, N. (1993). Bayley scales of infant development (2nd ed.). San Antonio, TX: The Psychological Corporation.Google Scholar
Bayley, N. (2006). Bayley scales of infant and toddler development (3rd ed.). San Antonio, TX: The Psychological Corporation.Google Scholar
Cattell, P. (1940). Cattell infant intelligence scale. New York, NY: The Psychological Corporation.Google Scholar
Flynn, J.R. (1999). Searching for justice: The discovery of IQ gains over time. American Psychologist, 54, 520.Google Scholar
Griffiths, R. (1996). Griffiths infant development scale-revised. Oxford, UK: Hogrefe.Google Scholar
Knobloch, H., Stevens, F., & Malone, A.E. (1980). Manual of developmental diagnosis. New York, NY: Harper and Row.Google Scholar
Lynn, R. (2009). What has caused the Flynn effect? Secular increases in the developmental quotients of infants. Intelligence, 37, 1624.Google Scholar
Mullen, E.M. (1995). Mullen scales of early learning: AGS edition. Circle Pines, MN: American Guidance Service.Google Scholar
Newborg, J. (2005). Battelle developmental inventory (2nd ed.). Itasca, IL: Riverside Publishing.Google Scholar
Stancin, T., & Aylward, G.P. (2008). Assessment of development and behavior. In Wolraich, M.L., Drotar, D.D., Dworkin, P.H., & Perrin, E.C. (Eds.), Developmental–behavioral pediatrics: Evidence and practice (pp. 144177). Philadelphia, PA: Mosby/Elsevier.Google Scholar

Further reading

Breakwell, G., Hammond, S.M., Fife-Schaw, C., & Smith, J.A. (Eds.) (2012). Research methods in psychology (4th ed.). London, UK: Sage.Google Scholar
Field, A., & Hole, G. (2003). How to design and report experiments. London, UK: Sage.Google Scholar

References

Baron-Cohen, S., Leslie, A.M., & Frith, U. (1985). Does the autistic child have a “theory of mind”? Cognition, 21, 3746.Google Scholar
Campbell, D.T., & Stanley, J.C. (1966). Experimental and quasi-experimental designs for research. Chicago, IL: Rand McNally.Google Scholar
Clarke, P.J., Snowling, M.J., Truelove, E., & Hulme, C. (2010). Ameliorating children’s reading comprehension difficulties: A randomised controlled trial. Psychological Science, 21, 11061116.Google Scholar
Clements, W.A., & Perner, J. (1994). Implicit understanding of belief. Cognitive Development, 9, 377395.Google Scholar
Duff, F.J., & Clarke, P.J. (2011). Practitioner Review: Reading disorders: What are the effective interventions and how should they be implemented and evaluated? Journal of Child Psychology and Psychiatry, 52, 312.Google Scholar
Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th ed.). London, UK: Sage.Google Scholar
Hanania, R., & Smith, L.B. (2010). Selective attention and attention switching: Towards a unified developmental approach. Developmental Science, 13, 622635.Google Scholar
Kohnen, S., Nickels, L., Brunsdon, R., & Coltheart, M. (2008). Patterns of generalisation after treating sub-lexical spelling deficits in a child with mixed dysgraphia. Journal of Research in Reading, 31, 157177.Google Scholar
Mill, J.S. (1882). A system of logic, ratiocinative and inductive: Being a connected view of the principles of evidence and the methods of scientific investigation (8th ed.). New York, NY: Harper and Brothers. Available online from: www.archive.org/details/systemofratiocin00milluoft.Google Scholar
Onishi, K.H., & Baillargeon, R. (2005). Do 15-month-old infants understand false beliefs? Science, 308, 255258.Google Scholar
Pollitt, E., & Mathews, R. (1998). Breakfast and cognition: An integrative summary. American Journal of Clinical Nutrition, 67, 804S813S.Google Scholar
Rosenthal, R. (1994). Interpersonal expectancy effects: A 30-year perspective. Current Directions in Psychological Science, 3, 176179.Google Scholar
Ruffman, T., & Perner, J. (2005). Do infants really understand false belief? Trends in Cognitive Sciences, 9, 462463.Google Scholar
Tabibi, Z., & Pfeffer, K. (2007). Finding a safe place to cross the road: The effect of distractors and the role of attention in children’s identification of safe and dangerous road-crossing sites. Infant and Child Development, 16, 193206.CrossRefGoogle Scholar
Wimmer, H., & Perner, J. (1983). Beliefs about beliefs: Representation and constraining function of wrong beliefs in young children’s understanding of deception. Cognition, 13, 103128.Google Scholar

Further reading

Duchowski, A. (2007). Eye tracking methodology: Theory and practice (Vol. 373). London, UK: Springer Science & Business Media.Google Scholar
Land, M., & Tatler, B. (2009). Looking and acting: Vision and eye movements in natural behaviour. Oxford, UK: Oxford University Press.Google Scholar

References

Castelhano, M.S., & Henderson, J.M. (2008). Stable individual differences across images in human saccadic eye movements. Canadian Journal of Experimental Psychology/Revue Canadienne de Psychologie Expérimentale, 62, 114.Google Scholar
Colombo, J., & Mitchell, D.W. (1990). Individual differences in early visual attention: Fixation time and information processing. In Colombo, J. & Fagen, J. (Eds.), Individual differences in infancy: Reliability, stability, prediction (pp. 193227). Hillsdale, NJ: Erlbaum.Google Scholar
Frank, M.C., Vul, E., & Johnson, S.P. (2009). Development of infants’ attention to faces during the first year. Cognition, 110, 160170.Google Scholar
Gredebäck, G., Johnson, S., & von Hofsten, C. (2009). Eye tracking in infancy research. Developmental Neuropsychology, 35, 119.Google Scholar
Henderson, J.M. (2003). Human gaze control during real-world scene perception. Trends in Cognitive Sciences, 7, 498504.Google Scholar
Holmqvist, K., Nyström, M., Andersson, R., Dewhurst, R., Jarodzka, H., & van de Weijer, J. (2011). Eye tracking: A comprehensive guide to methods and measures. Oxford, UK: Oxford University Press.Google Scholar
Johnson, M.H. (2011). Developmental cognitive neuroscience (3rd ed.). Oxford, UK: Wiley-Blackwell.Google Scholar
Johnson, M.H., Posner, M.I., & Rothbart, M.K. (1991). Components of visual orienting in early infancy: Contingency learning, anticipatory looking, and disengaging. Journal of Cognitive Neuroscience, 3, 335344.Google Scholar
Oakes, L.M. (2012). Advances in eye tracking in infancy research. Infancy, 17, 18.Google Scholar
Papageorgiou, K., Smith, T.J., Wu, R., Johnson, M.H., Kirkham, N.Z., & Ronald, A. (2014). Individual differences in infant fixation duration relate to attention and behavioral control in childhood. Psychological Science, 25, 13711379.Google Scholar
Rayner, K. (1998). Eye movements in reading and information processing: 20 years of research. Psychological Bulletin, 124, 372.Google Scholar
Saez de Urabain, I.R., Johnson, M.H., & Smith, T.J. (2014). GraFIX: A semiautomatic approach for parsing low- and high-quality eye-tracking data. Behavior Research Methods, 47, 5372.Google Scholar
Salapatek, P., Bechtold, A.G., & Bushnell, E.W. (1976). Infant visual acuity as a function of viewing distance. Child Development, 47, 860863.Google Scholar
Wade, N., & Tatler, B.W. (2005). The moving tablet of the eye: The origins of modern eye movement research. New York, NY: Oxford University Press.Google Scholar
Wass, S.V., & Smith, T.J. (2014). Individual differences in infant oculomotor behavior during the viewing of complex naturalistic scenes. Infancy, 19, 352384.Google Scholar
Wass, S.V., Smith, T.J., & Johnson, M.H. (2013). Parsing eye-tracking data of variable quality to provide accurate fixation duration estimates in infants and adults. Behavior Research Methods, 45, 229–250.CrossRefGoogle Scholar

Further reading

Hari, R., & Salmelin, R. (2012). Magnetoencephalography: From SQUIDs to neuroscience. NeuroImage, 61, 386–96.Google Scholar
Papadelis, C., Grant, P.E., Okada, Y., & Preissl, H. (2015). Editorial on emerging neuroimaging tools for studying normal and abnormal human brain development. Frontiers in Human Neuroscience, 9, 127.Google Scholar
Supek, S., & Aine, C.J. (2014). Magnetoencephalography, Berlin: Springer.CrossRefGoogle Scholar

References

Alem, O., Sander, T.H., Mhaskar, R., LeBlanc, J., Eswaran, H., Steinhoff, U., … Knappe, S. (2015). Fetal magnetocardiography measurements with an array of microfabricated optically pumped magnetometers. Physics in Medicine and Biology, 60, 47974811.Google Scholar
Baillet, S., Mosher, J.C., & Leahy, R.M. (2001). Electromagnetic brain mapping. IEEE Signal Processing Magazine, 18, 1430.Google Scholar
Blum, T., Saling, E., & Bauer, R. (1985). First magnetoencephalographic recordings of the brain activity of the human fetus. British Journal of Obstetrics and Gynaecology, 92, 12241229.Google Scholar
Cohen, D. (1968). Magnetoencephalography: Evidence of magnetic fields produced by alpha-rhythm currents. Science, 161, 784786.Google Scholar
Leader, L.R., Baillie, P., Martin, B., Molteno, C., & Wynchank, S. (1984). Fetal responses to vibrotactile stimulation, a possible predictor of fetal and neonatal outcome. Australian and New Zealand Journal of Obstetrics and Gynaecology, 24, 251256.Google Scholar
Linder, K., Schleger, F., Ketterer, C., Fritsche, L., Kiefer-Schmidt, I., Hennige, A., … Fritsche, A. (2014). Maternal insulin sensitivity is associated with oral glucose-induced changes in fetal brain activity. Diabetologia, 57, 11921198.Google Scholar
May, L.E., Suminski, R.R., Berry, A., Langaker, M.D., & Gustafson, K.M. (2014). Maternal physical activity mode and fetal heart outcome. Early Human Development, 90, 365369.Google Scholar
McCubbin, J., Robinson, S.E., Cropp, R., Moiseev, A., Vrba, J., Murphy, P., … Eswaran, H. (2006). Optimal reduction of MCG in fetal MEG recordings. IEEE Transactions on Biomedical Engineering, 53, 17201724.Google Scholar
Micheli, C., McCubbin, J., Murphy, P., Eswaran, H., Lowery, C.L., Ortiz, E., & Preissl, H. (2010). Verification of fetal brain responses by coregistration of fetal ultrasound and fetal magnetoencephalography data. Neuroimage, 49, 14691478.Google Scholar
Moraru, L., Sameni, R., Schneider, U., Haueisen, J., Schleussner, E., & Hoyer, D. (2011). Validation of fetal auditory evoked cortical responses to enhance the assessment of early brain development using fetal MEG measurements. Physiological Measurement, 32, 18471868.Google Scholar
Muenssinger, J., Matuz, T., Schleger, F., Kiefer-Schmidt, I., Goelz, R., Wacker-Gussmann, A., … Preissl, H. (2013). Auditory habituation in the fetus and neonate: A fMEG study. Developmental Science, 16, 287295.Google Scholar
Okada, Y., Pratt, K., Atwood, C., Mascrenas, A., Reineman, R., Nurminen, J., & Paulson, D. (2006). BabySQUID: A mobile, high-resolution multichannel magnetoencephalography system for neonatal brain assessment. Review of Scientific Instruments, 77, 024301.Google Scholar
Papadelis, C., Ahtam, B., Nazarova, M., Nimec, D., Snyder, B., Grant, P.E., & Okada, Y. (2014). Cortical somatosensory reorganization in children with spastic cerebral palsy: A multimodal neuroimaging study. Frontiers in Human Neuroscience, 8, 725.Google Scholar
Papadelis, C., Harini, C., Ahtam, B., Doshi, C., Grant, E., & Okada, Y. (2013). Current and emerging potential for magnetoencephalography in pediatric epilepsy. Journal of Pediatric Epilepsy, 2, 7385.Google Scholar
Preissl, H. (2005). Magnetoencephalography. International Review of Neurobiology, Vol. 68. San Diego, CA: Elsevier.Google Scholar
Querleu, D., Renard, X., Boutteville, C., & Crepin, G. (1989). Hearing by the human fetus? Seminars in Perinatology, 13, 409420.Google Scholar
Sander, T.H., Preusser, J., Mhaskar, R., Kitching, J., Trahms, L., & Knappe, S. (2012). Magnetoencephalography with a chip-scale atomic magnetometer. Biomedical Optics Express, 3, 981990.Google Scholar
Schleger, F., Landerl, K., Muenssinger, J., Draganova, R., Reinl, M., Kiefer-Schmidt, I., … Preissl, H. (2014). Magnetoencephalographic signatures of numerosity discrimination in fetuses and neonates. Developmental Neuropsychology, 39, 316329.Google Scholar
Walker, D., Grimwade, J., & Wood, C. (1971). Intrauterine noise: A component of the fetal environment. American Journal of Obstetrics and Gynecology, 109, 9195.Google Scholar
Wilson, J.D., Govindan, R.B., Hatton, J.O., Lowery, C.L., & Preissl, H. (2008). Integrated approach for fetal QRS detection. IEEE Transactions on Biomedical Engineering, 55, 21902197.Google Scholar

Further reading

Chudleigh, T., & Thilaganathan, B. (Eds.) (2004). Obstetric ultrasound: How, why and when (3rd ed.). London, UK: Churchill Livingstone.Google Scholar
Coady, A.M., & Bower, S. (Eds.) (2014). Twining’s textbook of fetal abnormalities (2nd ed.). London, UK: Churchill Livingstone.Google Scholar
Malinger, G., Monteagudo, A., Pilu, G., Timor-Tritsch, I., & Toi, A. (2007). Sonographic examination of the fetal central nervous system: Guidelines for performing the “basic examination” and the “fetal neurosonogram”. Ultrasound in Obstetrics and Gynecology 29, 109116.Google Scholar

References

Abo-Yaqoub, S., Kurjak, A., Mohammed, A.B., Shadad, A., & Abdel-Maaboud, M. (2012). The role of 4-D ultrasonography in prenatal assessment of fetal neurobehaviour and prediction of neurological outcome. Journal of Maternal & Fetal Neonatal Medicine, 25, 231236.Google Scholar
Anderson, G.M., Jacobs-Stannard, A., Chawarska, K., Volkmar, F.R., & Kliman, H.J. (2007). Placental trophoblast inclusions in autism spectrum disorder. Biological Psychiatry, 61, 487491.Google Scholar
Baschat, A.A., Viscardi, R.M., Hussey-Gardner, B., Hashmi, N., & Harman, C. (2009). Infant neurodevelopment following fetal growth restriction: Relationship with antepartum surveillance parameters. Ultrasound in Obstetrics & Gynecology, 33, 4450.Google Scholar
Blair, E., de Groot, J., & Nelson, K.B. (2011). Placental infarction identified by macroscopic examination and risk of cerebral palsy in infants at 35 weeks of gestational age and over. American Journal of Obstetrics & Gynecology, 205, 124 e121–127.Google Scholar
Bonifacio, S.L., Glass, H.C., Vanderpluym, J., Agrawal, A.T., Xu, D., Barkovich, A.J., & Ferriero, D.M. (2011). Perinatal events and early magnetic resonance imaging in therapeutic hypothermia. Journal of Pediatrics, 158, 360365.Google Scholar
Chan, F.Y., Pun, T.C., Lam, P., Lam, C., Lee, C.P., & Lam, Y.H. (1996). Fetal cerebral Doppler studies as a predictor of perinatal outcome and subsequent neurologic handicap. Obstetrics & Gynecology, 87, 981988.Google Scholar
Donald, I., Macvicar, J., & Brown, T.G. (1958). Investigation of abdominal masses by pulsed ultrasound. Lancet, 1, 11881195.Google Scholar
Eixarch, E., Meler, E., Iraola, A., Illa, M., Crispi, F., Hernandez-Andrade, E., & Figueras, F. (2008). Neurodevelopmental outcome in 2-year-old infants who were small-for-gestational age term fetuses with cerebral blood flow redistribution. Ultrasound in Obstetrics & Gynecology, 32, 894899.Google Scholar
Figueras, F., Eixarch, E., Meler, E., Iraola, A., Figueras, J., Puerto, B., & Gratacos, E. (2008). Small-for-gestational-age fetuses with normal umbilical artery Doppler have suboptimal perinatal and neurodevelopmental outcome. European Journal of Obstetrics & Gynecology and Reproductive Biology, 136, 3438.Google Scholar
Griffiths, P.D., Porteous, M., Mason, G., Russell, S., Morris, J., Fanou, E.M., & Reeves, M.J. (2012). The use of in utero MRI to supplement ultrasound in the foetus at high risk of developmental brain or spine abnormality. British Journal of Radiology, 85, e1038–1045.Google Scholar
James, D.K., Telfer, F.M., Keating, N.A., Blair, M.E., Wilcox, M.A., & Chilvers, C. (2000). Reduced fetal movements and maternal medication: New pregnancy risk factors for neurodevelopmental disability in childhood. Journal of Obstetrics and Gynaecology, 20, 226234.Google Scholar
Laskin, M.D., Kingdom, J., Toi, A., Chitayat, D., & Ohlsson, A. (2005). Perinatal and neurodevelopmental outcome with isolated fetal ventriculomegaly: A systematic review. Journal of Maternal & Fetal Neonatal Medicine, 18, 289298.Google Scholar
Melchiorre, K., Bhide, A., Gika, A.D., Pilu, G., & Papageorghiou, A.T. (2009). Counseling in isolated mild fetal ventriculomegaly. Ultrasound in Obstetrics & Gynecology, 34, 212224.Google Scholar
Ouahba, J., Luton, D., Vuillard, E., Garel, C., Gressens, P., Blanc, N., & Oury, J.F. (2006). Prenatal isolated mild ventriculomegaly: Outcome in 167 cases. British Journal of Obstetrics & Gynaecology, 113, 10721079.Google Scholar
Proctor, L.K., Whittle, W.L., Keating, S., Viero, S., & Kingdom, J.C. (2010). Pathologic basis of echogenic cystic lesions in the human placenta: Role of ultrasound-guided wire localization. Placenta, 31, 11111115.Google Scholar
Savchev, S., Sanz-Cortes, M., Cruz-Martinez, R., Arranz, A., Botet, F., Gratacos, E., & Figueras, F. (2013). Neurodevelopmental outcome of full-term small-for-gestational-age infants with normal placental function. Ultrasound in Obstetrics & Gynecology, 42, 201206.Google Scholar
Scherjon, S., Briet, J., Oosting, H., & Kok, J. (2000). The discrepancy between maturation of visual-evoked potentials and cognitive outcome at five years in very preterm infants with and without hemodynamic signs of fetal brain-sparing. Pediatrics, 105, 385391.Google Scholar
Signorelli, M., Tiberti, A., Valseriati, D., Molin, E., Cerri, V., Groli, C., & Bianchi, U.A. (2004). Width of the fetal lateral ventricular atrium between 10 and 12 mm: A simple variation of the norm? Ultrasound in Obstetrics & Gynecology, 23, 1418.Google Scholar
Toal, M., Keating, S., Machin, G., Dodd, J., Adamson, S.L., Windrim, R.C., & Kingdom, J.C. (2008). Determinants of adverse perinatal outcome in high-risk women with abnormal uterine artery Doppler images. American Journal of Obstetrics & Gynecology, 198, 330 e1e7.Google Scholar
Valcamonico, A., Danti, L., Frusca, T., Soregaroli, M., Zucca, S., Abrami, F., & Tiberti, A. (1994). Absent end-diastolic velocity in umbilical artery: Risk of neonatal morbidity and brain damage. American Journal of Obstetrics & Gynecology, 170, 796801.Google Scholar
Vossbeck, S., de Camargo, O.K., Grab, D., Bode, H., & Pohlandt, F. (2001). Neonatal and neurodevelopmental outcome in infants born before 30 weeks of gestation with absent or reversed end-diastolic flow velocities in the umbilical artery. European Journal of Pediatrics, 160, 128134.Google Scholar
Walker, D.M., Marlow, N., Upstone, L., Gross, H., Hornbuckle, J., Vail, A., & Thornton, J.G. (2011). The Growth Restriction Intervention Trial: Long-term outcomes in a randomized trial of timing of delivery in fetal growth restriction. American Journal of Obstetrics & Gynecology, 204, 34 e31–39.Google Scholar
Whitby, E.H., Paley, M.N., Sprigg, A., Rutter, S., Davies, N.P., Wilkinson, I.D., & Griffiths, P.D. (2004). Comparison of ultrasound and magnetic resonance imaging in 100 singleton pregnancies with suspected brain abnormalities. British Journal of Obstetrics & Gynaecology, 111, 784792.Google Scholar
Wienerroither, H., Steiner, H., Tomaselli, J., Lobendanz, M., & Thun-Hohenstein, L. (2001). Intrauterine blood flow and long-term intellectual, neurologic, and social development. Journal of Obstetrics and Gynecology, 97, 449453.Google Scholar

Further reading

Aslin, R.N. (2007). What’s in a look? Developmental Science, 10, 4853.CrossRefGoogle ScholarPubMed
Franchak, J.M., & Adolph, K.E. (2010). Visually guided locomotion: Head-mounted eye-tracking of natural locomotion in children and adults. Vision Research, 50, 27662774.Google Scholar
Franchak, J.M., Kretch, K.S., Soska, K.C., Babcock, J.S., & Adolph, K.E. (2010). Head-mounted eye-tracking in infants’ natural interactions: A new method. Paper presented at the Proceedings of the 2010 Symposium on Eye Tracking Research and Applications, Austin, TX.Google Scholar
Smith, L., Yu, C., Yoshida, H., & Fausey, C.M. (2015). Contributions of head-mounted cameras to studying the visual environments of infants and young children. Journal of Cognition and Development, 16, 407419.Google Scholar

References

Aslin, R.N. (2011). Infant eyes: A window on cognitive development. Infancy, 17, 126140.CrossRefGoogle Scholar
Bambach, S., Franchak, J.M., Crandall, D.J., & Yu, C. (2014). Detecting hands in children’s egocentric views to understand embodied attention during social interaction. Proceedings of the 36th annual meeting of the Cognitive Science Society.Google Scholar
Corbetta, D., Guan, Y., & Williams, J.L. (2012). Infant eye-tracking in the context of goal-directed actions. Infancy, 17, 102125.Google Scholar
Franchak, J.M., & Yu, C. (2015). Visual–manual coordination in natural reaching of young children and adults. Proceedings of the 37th annual meeting of the Cognitive Science Society.Google Scholar
Franchak, J.M., Kretch, K.S., Soska, K.C., & Adolph, K.E. (2011). Head-mounted eye tracking: A new method to describe infant looking. Child Development, 82, 17381750.Google Scholar
Frank, M.C., Vul, E., & Johnson, S.P. (2009). Development of infants’ attention to faces during the first year. Cognition, 110, 160170.Google Scholar
Hayhoe, M.M., & Rothkopf, C.A. (2011). Vision in the natural world. WIREs Cognitive Science, 2, 158166.Google Scholar
Kretch, K.S., & Adolph, K.E. (2015). Active vision in passive locomotion: Real-world free viewing in infants and adults. Developmental Science, 18, 736750.Google Scholar
Kretch, K.S., Franchak, J.M., & Adolph, K.E. (2014). Crawling and walking infants see the world differently. Child Development, 85, 15031518.Google Scholar
Land, M.F. (2009). Vision, eye movements, and natural behavior. Visual Neuroscience, 26, 5162.Google Scholar
Oakes, L.M. (2010). Infancy guidelines for publishing eye-tracking data. Infancy, 15, 15.Google Scholar
Yu, C., & Smith, L.B. (2013). Joint attention without gaze following: Human infants and their parents coordinate visual attention to objects through eye-hand coordination. PLoS ONE, 8, e79659.Google Scholar

Further reading

Harcourt, D., & Sargeant, J. (2011). The challenges of conducting ethical research with children. Education Inquiry, 2, 42436.Google Scholar
Jacquez, F., Vaughn, L.M., & Wagner, E. (2013). Youth as partners, participants or passive recipients: A review of children and adolescents in community-based participatory research (CBPR). American Journal of Community Psychology, 51, 176189.Google Scholar
Loveridge, J. (Ed.) (2010). Involving children and young people in research in educational settings. New Zealand: Ministry of Education.Google Scholar
Thiessen, D. (2007). Researching student experiences in elementary and secondary school: An evolving field of study. In Thiessen, D. & Cook-Sather, A. (Eds.), International handbook of student experience in elementary and secondary school (pp. 176). Dordrecht, NL: Springer.Google Scholar
Tisdall, K.M., Davis, J.M., & Galagher, M. (2009). Researching with children and young people. London, UK: Sage.Google Scholar

References

Barker, J., & Weller, S. (2003). “Is it fun?” Developing children-centered research methods. International Journal of Sociology and Social Policy, 23, 3358.Google Scholar
Cameron, H. (2005). Asking the tough questions: A guide to ethical practices in interviewing young children. Early Child Development and Care, 175, 597610.Google Scholar
Coles, R. (2003). Children of crisis. New York, NY: Little, Brown & Company.Google Scholar
Elbers, E. (2004). Conversational asymmetry and the child’s perspective in developmental and educational research. International Journal of Disability Development and Education, 51, 201215.Google Scholar
Heary, C., & Hennessy, E. (2006). Focus groups versus individual interviews with children: A comparison of data. Irish Journal of Psychology, 27, 5868.Google Scholar
Hill, M. (2006). Children’s voices on ways of having a voice: Children’s and young people’s perspectives on methods used in research and consultation. Childhood: A Global Journal of Child Research, 13, 6989.Google Scholar
Lambert, V., & Glacken, M. (2011). Engaging with children in research: Theoretical and practical implications of negotiating informed consent/assent. Nursing Ethics, 18, 781801.Google Scholar
Marschall, A. (2013). Transforming subjectivity: When aiming for mutually transformative processes in research with children. Outlines: Critical Practice Studies, 14, 160183.Google Scholar
Morrison, K. (2013). Interviewing children in uncomfortable settings: 10 lessons for effective practice. Educational Studies, 39, 320337.Google Scholar
Phelan, S.K., & Kinsella, E.A. (2013). Picture this … safety, dignity, and voice-ethical research with children: Practical considerations for the reflexive researcher. Qualitative Inquiry, 19, 8190.Google Scholar
Piaget, J. (1929). The child’s conception of the world. London, UK: Routledge & Kegan Paul.Google Scholar
Powell, M.B., & Snow, P.C. (2007). Guide to questioning children during the free-narrative phase of an investigative interview. Australian Psychologist, 42, 5765.Google Scholar
Stone, W.L., & Lemanek, K.L. (1990). Developmental issues in children’s self-reports. In La Greca, A.M. (Ed.), Through the eyes of the child: Obtaining self-reports from children and adolescents (pp. 1856). Needham Heights, MA: Allyn & Bacon.Google Scholar
Zwiers, M.L., & Morrissette, P.J. (1999). Effective interviewing of children: A comprehensive guide for counselors and human service workers. Philadelphia, PA: Taylor & Francis.Google Scholar

Further reading

Bright, P. (Ed.) (2012). Neuroimaging: Methods. Rijeka, Croatia: InTech.Google Scholar
Cabeza, R., & Kingstone, A. (2006). Handbook of functional neuroimaging of cognition (Cognitive neuroscience, 2nd. ed.). New York, NY: Bradford Books.Google Scholar
Poldrack, R.A., Mumford, J.A., & Nichols, T.E. (2011). Handbook of functional MRI data analysis (1st ed.). Cambridge, UK: Cambridge University Press.Google Scholar
Rao, M.S., & Jacobson, M. (2005). Developmental neurobiology (4th ed.). New York, NY: Holt Rinehart & Winston.Google Scholar
Sporns, O. (2012). Discovering the human connectome (1st ed.). Cambridge, MA: MIT Press.Google Scholar

References

Arichi, T., Fagiolo, G., Varela, M., Melendez-Calderon, A., Allievi, A., Merchant, N., … Edwards, A.D. (2012). Development of BOLD signal hemodynamic responses in the human brain. NeuroImage, 63, 663673.Google Scholar
Biswal, B., Yetkin, F.Z., Haughton, V.M., & Hyde, J.S. (1995). Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magnetic Resonance in Medicine, 34, 537541.Google Scholar
Cao, M., Wang, J.H., Dai, Z.J., Cao, X.Y., Jiang, L.L., Fan, F.M., … He, Y. (2014). Topological organization of the human brain functional connectome across the lifespan. Developmental Cognitive Neuroscience, 7, 7693.Google Scholar
Di Martino, A., Fair, D.A., Kelly, C., Satterthwaite, T.D., Castellanos, F.X., Thomason, M.E., … Milham, M.P. (2014). Unraveling the miswired connectome: A developmental perspective. Neuron, 83, 13351353.Google Scholar
Durston, S., & Casey, B.J. (2006). A shift from diffuse to focal cortical activity with development: The authors’ reply. Developmental Science, 9, 1820.Google Scholar
Goddings, A.L., Mills, K.L., Clasen, L.S., Giedd, J.N., Viner, R.M., & Blakemore, S.J. (2014). The influence of puberty on subcortical brain development. NeuroImage, 88, 242251.Google Scholar
Gogtay, N., Giedd, J.N., Lusk, L., Hayashi, K.M., Greenstein, D., Vaituzis, A.C., … Thompson, P.M. (2004). Dynamic mapping of human cortical development during childhood through early adulthood. Proceedings of the National Academy of Sciences, 101, 81748179.Google Scholar
Habas, P.A., Scott, J.A., Roosta, A., Rajagopalan, V., Kim, K., Rousseau, F., … Studholme, C. (2012). Early folding patterns and asymmetries of the normal human brain detected from in utero MRI. Cerebral Cortex, 22, 1325.Google Scholar
Hasan, K.M., Sankar, A., Halphen, C., Kramer, L.A., Brandt, M.E., Juranek, J., … Ewing-Cobbs, L. (2007). Development and organization of the human brain tissue compartments across the lifespan using diffusion tensor imaging. Neuroreport, 18, 17351739.Google Scholar
Kang, H.C., Burgund, E.D., Lugar, H.M., Petersen, S.E., & Schlaggar, B.L. (2003). Comparison of functional activation foci in children and adults using a common stereotactic space. NeuroImage, 19, 1628.Google Scholar
Kasprian, G., Brugger, P.C., Weber, M., Krssak, M., Krampl, E., Herold, C., & Prayer, D. (2008). In utero tractography of fetal white matter development. NeuroImage, 43, 213224.Google Scholar
Kundu, P., Inati, S.J., Evans, J.W., Luh, W.M., & Bandettini, P.A. (2012). Differentiating BOLD and non-BOLD signals in fMRI time series using multi-echo EPI. NeuroImage, 60, 17591770.Google Scholar
Nagy, Z., Westerberg, H., & Klingberg, T. (2004). Maturation of white matter is associated with the development of cognitive functions during childhood. Journal of Cognitive Neuroscience, 16, 12271233.Google Scholar
Scott, J.A., Hamzelou, K.S., Rajagopalan, V., Habas, P.A., Kim, K., Barkovich, A.J., … Studholme, C. (2012). 3D morphometric analysis of human fetal cerebellar development. Cerebellum, 11, 761770.Google Scholar
Thomason, M.E., Burrows, B.E., Gabrieli, J.D., & Glover, G.H. (2005). Breath holding reveals differences in fMRI BOLD signal in children and adults. NeuroImage, 25, 824837.Google Scholar
Thomason, M.E., Race, E., Burrows, B., Whitfield-Gabrieli, S., Glover, G.H., & Gabrieli, J.D. (2009). Development of spatial and verbal working memory capacity in the human brain. Journal of Cognitive Neuroscience, 21, 316332.Google Scholar
Thomason, M.E., Dennis, E.L., Joshi, A.A., Joshi, S.H., Dinov, I.D., Chang, C., … Gotlib, I.H. (2011). Resting-state fMRI can reliably map neural networks in children. NeuroImage, 55, 165175.Google Scholar
Thomason, M.E., Grove, L.E., Lozon, T.A., Jr., Vila, A.M., Ye, Y., Nye, M.J., … Romero, R. (2015). Age-related increases in long-range connectivity in fetal functional neural connectivity networks in utero. Developmental Cognitive Neuroscience, 11, 96104.Google Scholar
Thompson, P.M., Giedd, J.N., Woods, R.P., MacDonald, D., Evans, A.C., & Toga, A.W. (2000). Growth patterns in the developing brain detected by using continuum mechanical tensor maps. Nature, 404, 190193.Google Scholar

Further reading

Aslin, R.N. (2012). Questioning the questions that have been asked about the infant brain using near-infrared spectroscopy. Cognitive Neuropsychology, 29, 733.Google Scholar
Jöbsis-VanderVliet, F.F. (1999). Discovery of the near-infrared window into the body and the early development of near-infrared spectroscopy. Journal of Biomedical Optics, 4, 392.Google Scholar
Obrig, H., & Villringer, A. (2003). Beyond the visible: Imaging the human brain with light. Journal of Cerebral Blood Flow & Metabolism, 23, 118.Google Scholar

References

Blasi, A., Lloyd-Fox, S., Johnson, M.H., & Elwell, C.E. (2014). Test–retest reliability of fNIRS in infants. Neurophotonics. 1, 025005, 112.Google Scholar
Boas, D.A., Elwell, C.E., Ferrari, M., & Taga, G. (2014). Twenty years of functional near-infrared spectroscopy: Introduction for the special issue. NeuroImage, 85, 15.Google Scholar
Brazy, J.E., Lewis, D.V., Mitnick, M.H., & Jöbsis-VanderVliet, F.F. (1985). Noninvasive monitoring of cerebral oxygenation in preterm infants: Preliminary observations. Pediatrics, 75, 217225.Google Scholar
Cristia, A., Dupoux, E., Hakuna, Y., Lloyd-Fox, S., Schuetze, M., Kivits, J., ... Minagawa-Kawai, Y. (2012). An online database of infant functional Near InfraRed Spectroscopy studies: A community-augmented systematic review. PLoS ONE, 8, e58906.Google Scholar
Duncan, A., Meek, J.H., Clemence, M., Elwell, C.E., Tyszczuk, L., Cope, M., & Delpy, D. (1995). Optical pathlength measurements on adult head, calf and forearm and the head of the newborn infant using phase resolved optical spectroscopy. Physics in Medicine and Biology, 40, 295.Google Scholar
Ferrari, M., & Quaresima, V. (2012). A brief review on the history of human functional near-infrared spectroscopy (fNIRS) development and fields of application. NeuroImage, 63, 921935.Google Scholar
Fukui, Y., Ajichi, Y., & Okada, E. (2003). Monte Carlo prediction of near-infrared light propagation in realistic adult and neonatal head models. Applied Optics, 42, 28812887.Google Scholar
Gervain, J., Mehler, J., Werker, J.F., Nelson, C.A., Csibra, G., Lloyd-Fox, S., Shukla, M., & Aslin, R.A. (2011). Near infrared spectroscopy: A report from the McDonnell Infant Methodology Consortium. Developmental Cognitive Neuroscience, 1, 2246.Google Scholar
Jöbsis-VanderVliet, F.F. (1977). Noninvasive, infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters. Science, 198, 12641267.Google Scholar
Lloyd-Fox, S., Blasi, A., & Elwell, C.E. (2010). Illuminating the developing brain: The past, present and future of functional near infrared spectroscopy. Neuroscience & Biobehavioral Reviews, 34, 269284.Google Scholar
Lloyd-Fox, S., Wu, R., Richards, J.E., Elwell, C.E., & Johnson, M.H. (2013a). Cortical activation to action perception is associated with action production abilities in young infants. Cerebral Cortex, 25, 289297.Google Scholar
Lloyd-Fox, S., Blasi., A., Elwell, C.E., Charman, T., Murphy, D., & Johnson, M.H. (2013b). Reduced neural sensitivity to social stimuli in infants at-risk for autism. Proceedings of the Royal Society, B. 280, 20123026, 19.Google Scholar
Lloyd-Fox, S., Richards, J.E., Blasi, A., Murphy, D.G.M., Elwell, C.E., & Johnson, M.H. (2014a). Co-registering fNIRS with underlying cortical areas in infants. Neurophotonics, 1, 025006, 116.Google Scholar
Lloyd-Fox, S., Papademetriou, M., Darboe, M.K., Everdell, N.L., Wegmuller, R., Prentice, A.M., Moore, S.E., & Elwell, C.E. (2014b). Functional near infrared spectroscopy (fNIRS) to assess cognitive function in infants in rural Africa. Nature Scientific Reports, 4, 4740, 18.Google Scholar
Meek, J.H., Firbank, M., Elwell, C.E., Atkinson, J., Braddick, O., & Wyatt, J.S. (1998). Regional hemodynamic responses to visual stimulation in awake infants. Pediatric Research, 43, 840843.Google Scholar
Nagamitsu, S., Yamashita, Y., Tanaka, H., & Matsuishi, T. (2012). Functional near-infrared spectroscopy studies in children. BioPsychoSocial Medicine, 6, 7.Google Scholar
Salamon, G., Raynaud, C., Regis, J., & Rumeau, C. (1990). Magnetic resonance imaging of the pediatric brain. New York, NY: Raven Press.Google Scholar

Further reading

Bakeman, R., & Gottman, J.M. (1997). Observing interaction: An introduction to sequential analysis (2nd ed.). New York, NY: Cambridge University Press.Google Scholar
Bakeman, R., & Quera, V. (2011). Sequential analysis and observational methods for behavioral sciences. New York, NY: Cambridge University Press.Google Scholar
Cone, J.D. (1999). Observational assessment: Measure development and research issues. In Kendall, P.C., Butcher, J.N., & Holmbeck, G.N. (Eds.), Handbook of research methods in clinical psychology (2nd ed., pp. 183223). Hoboken, NJ: Wiley.Google Scholar
Hartmann, D.P., & Wood, D.D. (1982). Observational methods. In Bellack, A.S., Hersen, M., & Kazdin, A.E. (Eds.), International handbook of behavior modification and therapy (pp. 107138). New York, NY: Plenum Press.Google Scholar
Yoder, P., & Symons, F. (2010). Observational measurement of behavior. New York, NY: Springer.Google Scholar

References

Barker, C., Pistrang, N., & Elliott, R. (2010). Research methods in clinic psychology: An introduction for students and practitioner (2nd ed.). New York, NY: Wiley.Google Scholar
Bayley, N. (2005). Bayley scales of infant and toddler development (3rd ed., Bayley-III®). San Antonio, TX: Pearson.Google Scholar
Blount, R.L., Corbin, S.M., Sturges, J.W., Wolfe, V.V., Prater, J.M., & Jags, L.D. (1989). The relationship between adults’ behavior and child coping and distress during BMA/LP procedures: A sequential analysis. Behavior Therapy, 20, 585601.Google Scholar
Breau, L.M., McGrath, P.J., Camfield, C.S., & Finley, G.A. (2002). Psychometric properties of the non-communicating children’s pain checklist-revised. Pain, 99, 349357.Google Scholar
Chorney, J.M., McMurtry, C.M., Chambers, C.T., & Bakeman, R. (2015). Developing and modifying behavioral coding schemes in pediatric psychology: A practical guide. Journal of Pediatric Psychology, 40, 154164.Google Scholar
Cohen, L.L., Blount, R.L., & Panopoulos, G. (1997). Nurse coaching and cartoon distraction: An effective and practical intervention to reduce child, parent, and nurse distress during immunizations. Journal of Pediatric Psychology, 22, 355370.Google Scholar
Gardner, F. (2000). Methodological issues in the direct observation of parent–child interaction: Do observational findings reflect the natural behavior of participants? Clinical Child and Family Psychology Review, 3, 185198.Google Scholar
Gram, M. (2010). Self-reporting vs. observation: Some cautionary examples from parent/child food shopping behaviour. International Journal of Consumer Studies, 34, 394399.Google Scholar
Lord, C., Rutter, M., DiLavore, P.C., Risi, S., & Gotham, K. (2012). Autism diagnostic observation schedule (2nd ed.). Los Angeles, CA: Western Psychological Services.Google Scholar
Masling, J., & Stern, G. (1969). Effect of the observer in the classroom. Journal of Educational Psychology, 60, 351354.Google Scholar
Noldus Information Technology (2015). FaceReader with The Observer XT. Leesburg, VA: Noldus Information Technology Inc.Google Scholar
Pearson (2014). Wechsler intelligence scale for children (5th ed.). San Antonio, TX: Pearson.Google Scholar
Podsakoff, P.M., MacKenzie, S.B., & Lee, J. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88, 879903.Google Scholar
Rutter, M., Bishop, D., Pine, D., Scott, S., Stevenson, J.S., Taylor, E.A., & Thapar, A. (2011). Rutter’s child and adolescent psychiatry (5th ed.). New York, NY: Wiley.Google Scholar
Zisser, A., & Eyberg, S.M. (2010). Treating oppositional behavior in children using parent–child interaction therapy. In Kazdin, A.E. & Weisz, J.R. (Eds.), Evidence-based psychotherapies for children and adolescents (2nd ed., pp. 179193). New York, NY: Guilford Press.Google Scholar

Further reading

Childstats (2013). Memos on measures of social–emotional development in early childhood. Washington, DC. Retrieved from www.childstats.gov/pdf/Memos.pdf.Google Scholar
Merrell, K. (2007). Behavioral, social, and emotional assessment of children and adolescents (3rd ed.). Mahwah, NJ: Erlbaum.Google Scholar
National Research Council (2008). Early childhood assessment: Why, what, and how. Washington, DC: National Academies Press.Google Scholar
Yang, K. (2014). Categorical data analysis. London, UK: Sage Publications.Google Scholar

References

Achenbach, T.M. (2009). The Achenbach system of empirically based assessment (ASEBA): Development, findings, theory, and applications. Burlington, VT: University of Vermont Research Center for Children, Youth, & Families.Google Scholar
Ahadi, S.A., Rothbart, M.K., & Ye, R. (1993). Children's temperament in the US and China: Similarities and differences. European Journal of Personality, 7, 359377.Google Scholar
Arnett, J. (1989). Caregivers in day-care centers: Does training matter? Journal of Applied Developmental Psychology, 10, 541552.Google Scholar
Block, J.H. (1965). Child rearing practices report. Berkeley, CA: Institute of Human Development, University of California, Berkeley.Google Scholar
Bradley, R.H., Corwyn, R.F., Burchinal, M., McAdoo, H.P., & Garcia Coll, C. (2001a). The home environments of children in the United States. Part 2: Relations with behavioral development through age 13. Child Development, 72, 18681886.Google Scholar
Bradley, R.H., Corwyn, R.F., McAdoo, H.P., & Garcia Coll, C. (2001b). The home environments of children in the United States. Part 1: Variations by age, ethnicity, and poverty status. Child Development, 72, 18441867.Google Scholar
Caldwell, B.M., & Bradley, R.H. (2003). Home observation for measurement of the environment: Administration manual. Tempe, AZ: Family & Human Dynamics Research Institute, Arizona State University.Google Scholar
Charlesworth, R., Hart, C.H., Burts, D.C., Thomasson, R.H., Mosley, J., & Fleege, P.O. (1993). Measuring the developmental appropriateness of kindergarten teachers’ beliefs and practices. Early Childhood Research Quarterly, 8, 255276.Google Scholar
Gresham, F., & Elliot, S.N. (2008). Social skills improvement system. New York, NY: Pearson.Google Scholar
Fenson, L., Marchman, V.A., Thal, D.J., Dale, P.S., Reznick, J.S., & Bates, E. (2007). MacArthur-Bates child development inventory. Baltimore, MD: Brookes.Google Scholar
Robins, D., Fein, D., & Barton, M. (1999). The modified checklist for autism in toddlers (M-CHAT). Storrs, CT: University of Connecticut.Google Scholar
Rothbart, M.K., Ahadi, S.A., Hershey, K.L., & Fisher, P. (2001). Investigations of temperament at 3–7 years: The children's behavior questionnaire. Child Development, 72, 13941408.Google Scholar
Sherbow, A., Kettler, R.J., Elliot, S.N., Davies, M., & Dembitzer, L. (2015). Australian students: A comparative analysis of test psychometrics to the US normative sample. School Psychology International, 36, 313321.Google Scholar
Squires, J., Bricker, D., Twombly, E., & Potter, L. (2009). Ages and stages questionnaire user's guide (3rd ed.): A parent-completed child-monitoring system. Baltimore, MD: Brookes.Google Scholar

Further reading

Hatch, J.A. (Ed.) (2007). Early childhood qualitative research. London, UK: Taylor & Francis.Google Scholar
Packer, M.J. (2011). The science of qualitative research. New York, NY: Cambridge University Press.Google Scholar
Packer, M.J., & Cole, M. (in press). Culture in development. In Bornstein, M.H. & Lamb, M.E. (Eds.), Social and personality development: An advanced textbook (7th ed., pp. 85227). Hillsdale, NJ: Psychology Press.Google Scholar
Piaget, J. (1970). Structuralism. New York, NY: Harper & Row.Google Scholar

References

Atkinson, P., Delamont, S., & Hammersley, M. (1988). Qualitative research traditions: A British response to Jacob. Review of Educational Research, 58, 231250.Google Scholar
Bock, J., Gaskins, S., & Lancy, D.F. (2008). A four-field anthropology of childhood. Anthropology News, 4, 45.Google Scholar
Brown, L.M., Tappan, M.B., Gilligan, C., Miller, B.A., & Argyris, D.E. (1989). Reading for self and moral voice: A method for interpreting narratives of real- life moral conflict and choice. In Packer, M.J. & Addison, R.B. (Eds.), Entering the circle: Hermeneutic investigation in psychology (pp. 141164). Albany, NY: State University of New York Press.Google Scholar
Cole, M., Gay, J., Glick, J.A., & Sharp, D.W. (1971). The cultural context of learning and thinking. New York, NY: Basic Books.Google Scholar
Corsaro, W.A. (1982). Something old and something new: The importance of prior ethnography in the collection and analysis of audiovisual data. Sociological Methods and Research, 11, 145166.Google Scholar
Corsaro, W.A. (2006). Qualitative research on children’s peer relations in cultural context. In Chen, X., French, D.C., & Schneider, B.H. (Eds.), Peer relationships in cultural context (pp. 96122). Cambridge, UK: Cambridge University Press.Google Scholar
Darwin, C. (2002). The expression of the emotions in man and animals. New York, NY: Oxford University Press. (Original work published 1872.)Google Scholar
Gesell, A. (1934). An atlas of infant behavior: A systematic delineation of the forms and early growth of human behavior patterns. New Haven, CT: Yale University Press.Google Scholar
Gilligan, C. (1977). In a different voice: Women’s conception of the self and of morality. Harvard Educational Review, 47, 481517.Google Scholar
Goodwin, M.H. (1990). He-said-she-said: Talk as social organization among Black children. Bloomington, IN: Indiana University Press.Google Scholar
Hatch, J.A. (2002). Doing qualitative research in education settings. Albany, NY: State University of New York Press.Google Scholar
Hirschfeld, L.A. (2002). Why don’t anthropologists like children? American Anthropologist, 104, 611627.Google Scholar
Jacob, E. (1987). Qualitative research traditions: A review. Review of Educational Research, 57, 150.Google Scholar
Kohlberg, L. (1981). Essays on moral development. Vol 1: The philosophy of moral development: Moral stages and the idea of justice. New York, NY: Harper & Row.Google Scholar
Lewis, O. (2011). The children of Sanchez: Autobiography of a Mexican family. New York, NY: Random House. (Original work published 1961.)Google Scholar
Maxwell, J.A. (2004). Causal explanation, qualitative research, and scientific inquiry in education. Educational Researcher, 33, 311.Google Scholar
Mayer, S.J. (2005). The early evolution of Jean Piaget’s clinical method. History of Psychology, 8, 362.Google Scholar
Mead, M. (1928). Coming of age in Samoa: A psychological study of primitive youth for Western civilisation. New York, NY: William Morrow.Google Scholar
Mead, M. (1969). Research with human beings: A model derived from anthropological field practice. Daedalus, 98, 361386.Google Scholar
Piaget, J. (1960). The child’s conception of the world. London, UK: Routledge & Kegan Paul. (Original work published 1929.)Google Scholar
Sacks, H. (1992). Lectures of conversation (Vols. I and II). Oxford, UK: Basil Blackwell.Google Scholar
Schieffelin, B.B. (1990). The give and take of everyday life: Language socialization of Kaluli children. Cambridge, UK: Cambridge University Press.Google Scholar
Selman, R.L. (1981). The child as friendship philosopher. In Asher, S.R. & Gottman, J.M. (Eds.), The development of children’s friendships (pp. 242272). New York, NY: Cambridge University Press.Google Scholar
Smith, L.B., & Breazeal, C. (2007). The dynamic lift of developmental process. Developmental Science, 10, 6168.Google Scholar
Van der Smagt, T. (2006). Causation and constitution in system dynamics: Modelling a socially constituted world. Systems Research and Behavioral Science, 23, 513524.Google Scholar
Wacquant, L.J.D. (1995). The pugilistic point of view: How boxers think and feel about their trade. Theory and Society, 24, 489535.Google Scholar
Willis, P. (1977). Learning to labor: How working-class kids get working-class jobs. New York, NY: Columbia University Press.Google Scholar

Further reading

Bukowski, W.M., Newcomb, A.F., & Hartup, W.W. (1998). The company they keep: Friendships in childhood and adolescence. Cambridge, UK: Cambridge University Press.Google Scholar
Rubin, , Bukowski, K.H, , W., & Parker, J.G. (1998). Peer interactions, relationships, and groups. In Damon, W. & Eisenberg, N. (Eds.), Handbook of child psychology: Social, emotional, and personality development (Vol. 3, pp. 619700). New York, NY: Wiley.Google Scholar

References

Bukowski, W.M., & Hoza, B. (1989). Popularity and friendship: Issues in theory, measurement, and outcome. In Berndt, T.J. & Ladd, G.W. (Eds.), Peer relationships in child development (pp. 1545). New York, NY: Wiley.Google Scholar
Coie, J.D., Dodge, K.A., & Coppotelli, H. (1982). Dimensions and types of social status: A cross-age perspective. Developmental Psychology, 18, 557570.Google Scholar
De Los Reyes, A., & Prinstein, M.J. (2004). Applying depression-distortion hypotheses to the assessment of peer victimization in adolescents. Journal of Clinical Child and Adolescent Psychology, 33, 325335.Google Scholar
Harter, S. (1982). The perceived competence scale for children. Child Development, 53, 8797.Google Scholar
Harter, S. (2012). The construction of the self: A developmental perspective. New York, NY: Guilford Press.Google Scholar
Hodges, E.V.E., Boivin, M., Vitaro, F., & Bukowski, W.M. (1999). The power of friendship: Protection against an escalating cycle of peer victimization. Developmental Psychology, 35, 94101.Google Scholar
Hymel, S. (1986). Interpretations of peer behavior: Affective bias in childhood and adolescence. Child Development, 57, 431445.Google Scholar
Hymel, S., & Rubin, K.H. (1985). Children with peer relationship and social skills problems: Conceptual, methodological, and developmental issues. In Whitehurst, G.J. (Ed.), Annals of Child Development (Vol. 2). Greenwich, CT: JAI Press.Google Scholar
Hymel, S., Wagner, E., & Butler, L. (1990). Reputational bias: View from the peer group. In Asher, S.R. & Coie, J. (Eds.), Peer rejection in childhood (pp. 156186). Cambridge, UK: Cambridge University Press.Google Scholar
Masten, A.S., Morison, P., & Pellegrini, D.S. (1985). A Revised Class Play method of peer assessment. Developmental Psychology, 3, 523533.Google Scholar
Moreno, J.L. (1934). Who shall survive? A new approach to the problem of human interrelations. Washington, DC: Nervous and Mental Disease Publishing Co.Google Scholar
Prinstein, M.J., Boergers, J., & Vernberg, E.M. (2001). Overt and relational aggression in adolescents: Social-psychological adjustment of aggressors and victims. Journal of Clinical Child Psychology, 30, 479491.Google Scholar
Terry, R. (2000). Recent advances in measurement theory and the use of sociometric techniques. In Cillessen, A.H.N. & Bukowski, W.M. (Eds.), New directions for child and adolescent development (Vol. 88, pp. 311). San Francisco, CA: Jossey-Bass.Google Scholar
Velasquez, A.M., Santo, J.B., Saldarriaga, L.M., Lopez, L.S., & Bukowski, W.M. (2010). Context-dependent victimization and aggression differences between all-girl and mixed-sex schools. Merrill-Palmer Quarterly, 56, 283302.Google Scholar

Further reading

Johnson, J.G., Cohen, P., Kasen, S., Skodol, A., & Brook, J.S. (2000). Age-related change in personality disorder trait levels between early adolescence and adulthood: A community-based longitudinal investigation. Acta Psychiatrica Scandinavica, 102, 265275.Google Scholar
Werner, E.E., & Smith, R.S. (2001). Journeys from childhood to midlife: Risk, resilience and recovery. Ithaca, NY: Cornell University Press.Google Scholar

References

Giedd, J.N. (2015). The amazing teen brain. Scientific American, 312, 3237.Google Scholar
Kelsey, J.L., Whitemore, A.S., Evans, A.S., & Thompson, W.D. (1996). Methods in observational epidemiology (2nd ed.). Oxford, UK: Oxford University Press.Google Scholar
Pulkkinen, L., Virtanen, T., Klinteberg, B.A., & Magnusson, D. (2000). Child behavior and adult personality: Comparisons between criminality groups in Finland and Sweden. Criminal Behaviour & Mental Health, 10, 155169.Google Scholar
Richards, M., Hardy, R., Kuh, D., & Wadsworth, M. (2001). Birth weight and cognitive function in the British 1946 birth cohort: Longitudinal population based study. British Medical Journal, 322, 199203.Google Scholar

Further reading

Nesselroade, J.R., & Baltes, P.B. (Eds.) (1979). Longitudinal research in the study of behavior and development. London, UK: Academic Press.Google Scholar
Newsom, J.T. (2015). Longitudinal structural equation modelling. London, UK: Routledge.Google Scholar

Acknowledgment

Thank you to Claire Hughes for her comments on an earlier draft of this entry.

References

Allison, P.D. (2003). Missing data techniques for structural equation modelling. Journal of Abnormal Psychology, 112, 545–557.Google Scholar
Baltes, P.B., & Nesselroade, J.R. (1979). History and rationale of longitudinal research. In J.R. Nesselroade & P.B. Baltes (Eds.), Longitudinal research in the study of behavior and development (pp. 1–39). London, UK: Academic Press.Google Scholar
Brown, T.A. (2006). Confirmatory factor analysis for applied research. London, UK: Guilford Press.Google Scholar
Bryant, P. (1990). Empirical evidence for causes in development. In G. Butterworth & P. Bryant (Eds.), Causes of development: Interdisciplinary perspectives (pp. 33–45). London, UK: Harvester Wheatsheaf.Google Scholar
Duncan, T.E., & Duncan, S.C. (2004). An introduction to latent growth curve modelling. Behavior Therapy, 35, 333–363.Google Scholar
Graham, J.W. (2009). Missing data analysis: Making it work in the real world. Annual Review of Psychology, 60, 549–576.Google Scholar
Granger, C.W.J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37, 424–438.Google Scholar
Hertzog, C., & Nesselroade, J.R. (2003). Assessing psychological change in adulthood. Psychology and Aging, 18, 639–657.Google Scholar
Jeličić, H., Phelps, E., & Lerner, R.M. (2009). Use of missing data methods in longitudinal studies: The persistence of bad practices in developmental psychology. Developmental Psychology, 45, 1195–1199.Google Scholar
Kline, R.B. (2011). Principles and practice of structural equation modeling (3rd ed.). London, UK: Guilford Press.Google Scholar
Matson, J., Turygin, N.C., Beighley, J., & Matson, M.L. (2012). Status of single-case research designs for evidence-based practice. Research in Autism Spectrum Disorders, 6, 931–938.Google Scholar
Menard, S. (2002). Longitudinal research (2nd ed.). London: Sage.Google Scholar
Millsap, R.E. (2010). Testing measurement invariance using item response theory in longitudinal data: An introduction. Child Development Perspectives, 4, 5–9.Google Scholar
Rust, J., & Golombok, S. (2009). Modern psychometrics: The science of psychological assessment (3rd ed.). London, UK: Routledge.Google Scholar
Salthouse, T.A., & Nesselroade, J.R. (2010). Dealing with short-term fluctuation in longitudinal research. Journal of Gerontology: Psychological Sciences, 65B, 698–705.Google Scholar
Schafer, J.L., & Graham, J.W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7, 147–177.Google Scholar
Schaie, K.W. (1965). A general model for the study of developmental problems. Psychological Bulletin, 64, 92–107.Google Scholar
Schmidt, K.R.T., & Teti, D.M. (2006). Issues in the use of longitudinal and cross-sectional designs. In D.M. Teti (Ed.), Handbook of research methods in developmental science (pp. 3–20). Oxford, UK: Blackwell.Google Scholar
Siegler, R.S., & Crowley, K. (1991). The microgenetic method: A direct means for studying cognitive development. American Psychologist, 46, 606–620.Google Scholar
Twisk, J.W.R. (2003). Applied longitudinal data analysis for epidemiology: A practical guide. Cambridge, UK: Cambridge University Press.Google Scholar
Van Der Kamp, L., & Bijleveld, C. (1998). Methodological issues in longitudinal research. In Bijleveld, C., Van Der Kamp, L., Mooijaart, A., Van Der Kloot, W., Van Der Leeden, R., & Van Der Burg, E. (Eds.), Longitudinal data analysis: Designs, models and methods (pp. 1–45). London: Sage.Google Scholar

Further reading

Gillham, N.W. (2001). A life of Sir Francis Galton: From African exploration to the birth of eugenics. New York, NY: Oxford University Press.Google Scholar
Harris, J.R. (1998). The nurture assumption: Why children turn out the way they do. New York, NY: Free Press.Google Scholar
Pinker, S. (2002). The blank slate: The modern denial of human nature. New York, NY: Penguin.Google Scholar
Plomin, R., DeFries, J.C., Knopik, V.S., & Neiderhiser, J.M. (2013). Behavioral genetics. New York, NY: Worth.Google Scholar
Wright, L. (1997). Twins: And what they tell us about who we are. New York, NY: Wiley.Google Scholar

References

Bouchard, T.J., Jr., & Loehlin, J.C. (2001). Genes, evolution, and personality. Behavior Genetics, 31, 243273.Google Scholar
Bouchard, T.J., Jr., & McGue, M. (2003). Genetic and environmental influences on human psychological differences. Journal of Neurobiology, 54, 445.Google Scholar
Bouchard, T.J., Lykken, D.T., McGue, M., Segal, N.L., & Tellegen, A. (1990). Sources of human psychological differences: The Minnesota study of twins reared apart. Science, 250, 223228.Google Scholar
Darwin, C.R. (1859). On the origin of species by means of natural selection, or the preservation of favoured races in the struggle for life. London, UK: J. Murray.Google Scholar
Galton, F. (1869). Hereditary genius: An inquiry into its laws and consequences. London, UK: Macmillan.Google Scholar
Heston, L.L. (1966). Psychiatric disorders in foster home reared children of schizophrenic mothers. British Journal of Psychiatry, 112, 819825.Google Scholar
Johnson, W., Krueger, R.F., Bouchard, T.J., Jr., & McGue, M. (2002). The personalities of twins: Just ordinary folks. Twin Research, 5, 125131.Google Scholar
Kendler, K.S., Neale, M.C., Kessler, R.C., Heath, A.C., & Eaves, L.J. (1993). A test of the equal-environment assumption in twin studies of psychiatric illness. Behavior Genetics, 23, 2127.Google Scholar
McGue, M. (2010). The end of behavioral genetics? Behavior Genetics, 40, 284296.Google Scholar
McGue, M., & Bouchard, T.J. (1998). Genetic and environmental influences on human behavioral differences. Annual Review of Neuroscience, 21, 124.Google Scholar
McGue, M., Keyes, M., Sharma, A., Elkins, I., Legrand, L., Johnson, W., & Iacono, W.G. (2007). The environments of adopted and non-adopted youth: Evidence on range restriction from the Sibling Interaction and Behavior Study (SIBS). Behavior Genetics, 37, 449462.Google Scholar
Mednick, S.A., Gabrielli, W.F., Jr., & Hutchings, B. (1984). Genetic influences in criminal convictions: Evidence from an adoption cohort. Science, 224, 891894.Google Scholar
Plomin, R., Fulker, D.W., Corley, R., & DeFries, J.C. (1997). Nature, nurture and cognitive development: A parent–offspring adoption study. Psychological Science, 8, 442447.Google Scholar
Polderman, T.J., Benyamin, B., de Leeuw, C.A., Sullivan, P.F., van Bochoven, A., Visscher, P.M., & Posthuma, D. (2015). Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nature Genetics, 47, 702709.Google Scholar
Posthuma, D., De Geus, E.J., Bleichrodt, N., & Boomsma, D.I. (2000). Twin–singleton differences in intelligence? Twin Research, 3, 8387.Google Scholar
Rietveld, C.A., Esko, T., Davies, G., Pers, T.H., Turley, P., Benyamin, B., … Koellinger, P.D. (2014). Common genetic variants associated with cognitive performance identified using the proxy-phenotype method. Proceedings of the National Academy of Sciences, 111, 1379013794.Google Scholar
Rutter, M., Silberg, J., O’Connor, T., & Simonoff, E. (1999). Genetics and child psychiatry: I. Advances in quantitative and molecular genetics. Journal of Child Psychology and Psychiatry, 40, 318.Google Scholar
Stoolmiller, M. (1999). Implications of restricted range of family environments for estimates of heritability and nonshared environment in behavior-genetic adoption studies. Psychological Bulletin, 125, 392409.Google Scholar
Vrieze, S.I., Hicks, B.M., Iacono, W.G., & McGue, M. (2012). Decline in genetic influence on the co-occurrence of alcohol, marijuana, and nicotine dependence symptoms from age 14 to 29. American Journal of Psychiatry, 169, 10731081.Google Scholar
Wender, P.H., Rosenthal, D., Kety, S.S., Schulsinger, F., & Welner, J. (1974). Crossfostering: A research strategy for clarifying the role of genetic and experiential factors in the etiology of schizophrenia. Archives of General Psychiatry, 30, 121128.Google Scholar

Further reading

Gelman, A., & Hill, J. (2007). Data analysis using regression and multilevel/hierarchical models. New York, NY: Cambridge University Press.Google Scholar
Kruschke, J. (2015). Doing Bayesian data analysis: A tutorial with R, JAGS, and Stan. Oxford, UK: Academic Press.Google Scholar

References

Andrews, M., & Baguley, T. (2013). Prior approval: The growth of Bayesian methods in psychology. British Journal of Mathematical & Statistical Psychology, 66, 17.Google Scholar
Box, G.E.P., & Tiao, G.C. (1973). Bayesian inference in statistical analysis. New York, NY: Wiley.Google Scholar
Fisher, R.A. (1925). Statistical methods for research workers. Edinburgh, UK: Oliver & Boyd.Google Scholar
Gelman, A., Carlin, J., Stern, H., Dunson, D., Vehtari, A., & Rubin, D. (2014). Bayesian data analysis. New York, NY: Chapman and Hall/CRC.Google Scholar
Jeffreys, H. (1961). Theory of probability. Oxford, UK: Clarendon Press.Google Scholar
Koller, D., & Friedman, N. (2009). Probabilistic graphical models: Principles and techniques. Cambridge, MA: MIT Press.Google Scholar
Pearl, J. (1988). Probabilistic reasoning in intelligent systems: Networks of plausible inference. San Francisco, CA: Morgan Kaufmann.Google Scholar
Pearl, J. (2000). Causality: Models, reasoning, and inference. New York, NY: Cambridge University Press.Google Scholar
Rasmussen, C., & Williams, C. (2006). Gaussian processes for machine learning. Cambridge, MA: MIT Press.Google Scholar
Stigler, S.M. (1999). Statistics on the table: The history of statistical concepts and methods. Cambridge, MA: Harvard University Press.Google Scholar

Further reading

Elman, J.L. (2005). Connectionist models of cognitive development: Where next? Trends in Cognitive Sciences, 9, 111117.Google Scholar
Mareschal, D., & Thomas, M.S. (2007). Computational modeling in developmental psychology. IEEE Transactions on Evolutionary Computation, 11, 137150.Google Scholar
McClelland, J.L. (2013). Integrating probabilistic models of perception and interactive neural networks: A historical and tutorial review. Frontiers in Psychology, 4, 503.Google Scholar
Quinlan, P.T. (2003). Connectionist models of development. Hove, UK: Psychology Press.Google Scholar
Schlesinger, M., & McMurray, B. (2012). The past, present, and future of computational models of cognitive development. Cognitive Development, 27, 326348.Google Scholar

Acknowledgments

The writing of this entry was supported by the ESRC International Centre for Language and Communicative Development (LuCiD) at Lancaster University.

References

Bertoncini, J., Serniclaes, W., & Lorenzi, C. (2009). Discrimination of speech sounds based upon temporal envelope versus fine structure cues in 5- to 7-year-old children. Journal of Speech, Language, and Hearing Research, 52, 682695.Google Scholar
Chao, F., Lee, M.H., Jiang, M., & Changle, Z. (2014). An infant development-inspired approach to robot hand–eye coordination. International Journal of Advanced Robotic Systems, 11, 15.Google Scholar
Cohen, I.L. (1994). An artificial neural network analogue of learning in autism. Biological Psychiatry, 36, 520.Google Scholar
Elman, J.L. (1990). Finding structure in time. Cognitive Science, 14, 179211.Google Scholar
Harm, M.W., & Seidenberg, M.S. (1999). Phonology, reading acquisition, and dyslexia: Insights from connectionist models. Psychological Review, 106, 491528.Google Scholar
Jasso, H., Triesch, J., Deák, G., & Lewis, J.M. (2012). A unified account of gaze following. IEEE Transactions on Autonomous Mental Development, 4, 257272.Google Scholar
Kaas, J.H. (1997). Topographic maps are fundamental to sensory processing. Brain Research Bulletin, 44, 107112.Google Scholar
Li, P., Farkas, I., & MacWhinney, B. (2004). Early lexical development in a self-organizing neural network. Neural Networks, 17, 13451362.Google Scholar
Mareschal, D., & Westermann, G. (2010). Mixing the old with the new and the new with the old: Combining prior and current knowledge in conceptual change. In Johnson, S.P. (Ed.), Neoconstructivism: The new science of cognitive development (pp. 213229). New York, NY: Oxford University Press.Google Scholar
Mareschal, D., French, R.M., & Quinn, P.C. (2000). A connectionist account of asymmetric category learning in early infancy. Developmental Psychology, 36, 635645.Google Scholar
Mareschal, D., Johnson, M.H., Sirois, S., Spratling, M.W., Thomas, M., & Westermann, G. (2007). Neuroconstructivism: How the brain constructs cognition. Oxford, UK: Oxford University Press.Google Scholar
Rumelhart, D.E., Hinton, G.E., & Williams, R.J. (1986). Learning representations by back-propagating errors. Nature, 323, 533536.Google Scholar
Shultz, T.R. (2003). Computational developmental psychology. Cambridge, MA: MIT Press.Google Scholar
St Clair, M.C., Monaghan, P., & Christiansen, M.H. (2010). Learning grammatical categories from distributional cues: Flexible frames for language acquisition. Cognition, 116, 341360.Google Scholar
Thomas, M.S.C., Knowland, V.C.P., & Karmiloff-Smith, A. (2011). Mechanisms of developmental regression in autism and the broader phenotype: A neural network modeling approach. Psychological Review, 118, 637654.Google Scholar
Westermann, G. (2016). Experience-dependent brain development as a key to understanding the language system. Topics in Cognitive Science, 8, 446458.Google Scholar
Westermann, G., & Miranda, E.R. (2004). A new model of sensorimotor coupling in the development of speech. Brain and Language, 89, 393400.Google Scholar
Westermann, G., & Ruh, N. (2012). A neuroconstructivist model of past tense development and processing. Psychological Review, 119, 649667.Google Scholar

Further reading

Dobson, A.J. (1990). An introduction to generalized linear models. London, UK: Chapman & Hall.Google Scholar
von Eye, A., & Mun, E.-Y. (2013). Log-linear modeling: Concepts, interpretation and applications. New York, NY: Wiley.Google Scholar
von Eye, A., & Schuster, C. (1998). Regression analysis for the social sciences: Models and applications. San Diego, CA: Academic Press.Google Scholar
Wilcox, R.R. (2011). Modern statistics for the social and behavioral sciences: A practical introduction. Boca Raton, FL: CRC Press.Google Scholar

References

Berkovits, I., Hancock, G.R., & Nevitt, J. (2000). Bootstrap resampling approaches for repeated measures designs: Relative robustness to sphericity and normality violations. Educational and Psychological Measurement, 60, 877892.Google Scholar
Bock, R.D. (1975). Multivariate statistical methods in behavioral research. New York, NY: McGraw-Hill.Google Scholar
Finkelstein, J.W., von Eye, A., & Preece, M.A. (1994). The relationship between aggressive behavior and puberty in normal adolescents: A longitudinal study. Journal of Adolescent Health, 15, 319326.Google Scholar
Greenhouse, S.W., & Geisser, S. (1959). On methods in the analysis of profile data. Psychometrika, 24, 95112.Google Scholar
Hox, J.J. (2000). Multilevel analyses of grouped and longitudinal data. In Little, T.D., Schnabel, K.U., & Baumert, J. (Eds.), Modeling longitudinal and multilevel data (pp. 1532). Mahwah, NJ: Erlbaum.Google Scholar
Huynh, H., & Feldt, L.S. (1976). Estimation of the Box correction for degrees of freedom from sample data in randomised block and split-plot designs. Journal of Educational Statistics, 1, 6982.Google Scholar
Mauchly, J.W. (1940). Significance test for sphericity of a normal n-variate distribution. Annals of Mathematical Statistics, 11, 204209.Google Scholar
McCullagh, P., & Nelder, J.A. (1989). Generalized linear models (2nd ed.). London, UK: Chapman & Hall.Google Scholar
Neter, J., Kutner, M.H., Nachtsheim, C.J., & Wasserman, W. (1996). Applied linear statistical models. Chicago, IL: Irwin.Google Scholar
Rutherford, A. (2001). Introducing ANOVA and ANCOVA: A GLM approach. London, UK: Sage.Google Scholar
Schuster, C., & von Eye, A. (2001). The relationship of ANOVA models with random effects and repeated measurement designs. Journal of Adolescent Research, 16, 205220.Google Scholar
von Eye, A., & Wiedermann, W. (2015). General linear models for the analysis of single subject data and for the comparison of individuals. Journal for Person-Oriented Research, 1, 5671.Google Scholar
Wilcox, R.R., Keselman, H.J., Muska, J., & Cribbie, R. (2000). Repeated measures ANOVA: Some new results on comparing trimmed means and means. British Journal of Mathematical and Statistical Psychology, 53, 6982.Google Scholar
Wilcox, R.R., & Keselman, H.J. (2003). Repeated measures one-way ANOVA based on a modified one-step M-estimator. British Journal of Mathematical and Statistical Psychology, 56, 1525.Google Scholar

Further reading

Buros Center for Testing. (2014). The nineteenth mental measurements yearbook. Lincoln, NE: Buros Center for Testing. http://buros.org.Google Scholar
Glascoe, F.P., & Leew, S. (2010). Parenting behaviors, perceptions, and psychosocial risk: Impacts on young children’s development. Pediatrics, 125, 313319.Google Scholar
Gottfredson, L.S. (1994). The science and politics of race-norming. American Psychologist, 48, 955963.Google Scholar
International Test Commission. (2005). The ITC guidelines on adapting tests. www.intestcom.org/page/16.Google Scholar
Muennig, P., Schweinhart, L., Montie, J., & Neidell, M. (2009). Effects of a prekindergarten education intervention on adult health: 37-year follow-up results of a randomized controlled trial. American Journal of Public Health, 99, 14311437.Google Scholar
Reynolds, A.J., Temple, J.A., Ou, S.R., Arteaga, I., & White, B. (2011). School-based early childhood education and age-28 well-being: Effects by timing, dosage, and subgroups. Science, 333, 360364.Google Scholar
Sameroff, A.J., Seifer, R., Barocas, R., Zax, M., & Greenspan, S. (1987). Intelligence quotient scores of 4-year-old children: Social–environmental risk factors. Pediatrics, 79, 343350.Google Scholar

References

American Educational Research Association, American Psychological Association, & National Council on Measurement in Education. ( 2014). Standards for educational and psychological testing (3rd ed.). Washington, DC: American Educational Research Association.Google Scholar
Brixey, S., Siddique, I., Cohn, J., Johnson, S., Hamilton, C., Li, S., Simpson, P., & Meurer, J. (2009). Developmental screening in an urban pediatric clinic. Paper presented at the Pediatric Academic Societies Annual Meeting, Baltimore, Maryland, USA in May.Google Scholar
Buros Center for Testing. ( 2014). Standards, codes, and guidelines. Lincoln, NE: Buros Center for Testing.Google Scholar
Glascoe, F.P. (2001). Are over-referrals on developmental screening tests really a problem? Archives of Pediatrics and Adolescent Medicine, 155, 5459.Google Scholar
Glascoe, F.P. (2013). Collaborating with parents: Using parents’ evaluation of developmental status in early detection and intervention (2nd ed.). Nolensville, TN: PEDSTest.com.Google Scholar
Glascoe, F.P., Marks, K.P., Poon, J.K., & Macias, M.M. (Eds.) (2013). Identifying and addressing developmental and behavioral problems: A practical guide for medical and non-medical professionals, trainees, researchers and advocates. Nolensville, TN: PEDStest.com.Google Scholar
Glascoe, F.P., Marks, K.P., & Squires, J. (2012) Improving the definition of developmental delay. Journal of Developmental & Behavioral Pediatrics, 33, 87.Google Scholar
Glascoe, F.P., & Squires, J. (2009). Questions about the ability of broad-band screens to detect children with ASD. Journal of Developmental and Behavioral Pediatrics, 30, 174.Google Scholar
Hix-Small, H., Marks, K.P., Squires, J., & Nickel, R. (2007). Impact of implementing developmental screening at 12 and 24 months in a pediatric practice. Pediatrics, 120, 381389.Google Scholar
Majnemer, A. (Ed.) (2012). Measures of outcomes and their determinants for children and youth with developmental disabilities. London, UK: Mac Keith Press.Google Scholar
Marks, K.P. (2007). Should general pediatricians not select the Ages & Stages Questionnaire in light of the Rydz et al. study? Pediatrics, 120, 457458.Google Scholar
Murphy, C.O., & Davidshofer, K.R. (2005). Psychological testing: Principles and applications (6th ed.). Upper Saddle River, NJ: Pearson/Prentice Hall.Google Scholar
Roux, A.M., Herrera, P., Wold, C.M., Dunkle, M.C., Glascoe, F.P., & Shattuck, P.T. (2012). Reaching underserved children with autism screening: The 211LA developmental screening project. American Journal of Preventive Medicine, 43, 514530.Google Scholar
Schonwald, A., Huntington, N., Chan, E., Risko, W., & Bridgemohan, C. (2009). Routine developmental screening implemented in urban primary care settings: More evidence of feasibility and effectiveness. Pediatrics, 123, 660688.Google Scholar

Further reading

Bolker, B.M., Brooks, M.E., Clark, C.J., Geange, S.W., Poulsen, J.R., Stevens, M.H.H., & White, J.S.S. (2009). Generalized linear mixed models: A practical guide for ecology and evolution. Trends in Ecology & Evolution, 24, 127135.Google Scholar
Jaeger, T.F. (2008). Categorical data analysis: Away from ANOVAs (transformation or not) and towards logit mixed models. Journal of Memory and Language, 59, 434446.Google Scholar

References

Baayen, R.H., Davidson, D.J., & Bates, D.M. (2008). Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language, 59, 390412.Google Scholar
Barr, D.J., Levy, R., Scheepers, C., & Tily, H.J. (2013). Random effects structure for confirmatory hypothesis testing: Keep it maximal. Journal of Memory and Language, 68, 255278.Google Scholar
Bryk, A.S., & Raudenbush, S.W. (1992). Hierarchical linear models: Applications and data analysis methods. London, UK: Sage.Google Scholar
Clark, H.H. (1973). The language-as-fixed-effect fallacy: A critique of language statistics in psychological research. Journal of Verbal Learning and Verbal Behavior, 12, 335359.Google Scholar
Davies, R., Arnell, R., Birchenough, J.M.H., Grimmond, D., & Houlson, S. (in press). Reading through the lifespan: Individual differences in psycholinguistic effects. Journal of Experimental Psychology: Learning, Memory and Cognition.Google Scholar
Gelman, A. (2015). The connection between varying treatment effects and the crisis of unreplicable research: A Bayesian perspective. Journal of Management, 41, 632643.Google Scholar
Goldstein, H. (2011). Multilevel statistical models (4th ed.). Chichester, UK: Wiley.Google Scholar
Golino, H.F., & Gomes, C.M.A. (2014). Psychology data from the BAFACALO project: The Brazilian Intelligence Battery based on two state-of-the-art models – Carroll’s model and the CHC model. Journal of Open Psychology Data, 2, e6.Google Scholar
Judd, C.M., Westfall, J., & Kenny, D.A. (2012). Treating stimuli as a random factor in social psychology: A new and comprehensive solution to a pervasive but largely ignored problem. Journal of Personality and Social Psychology, 103, 5469.Google Scholar
Kreft, I., & de Leeuw, J. (1998). Introducing multilevel modeling. London, UK: Sage.Google Scholar
Pashler, H., & Wagenmakers, E.J. (2012). Editors’ introduction to the special section on Replicability in psychological science: A crisis of confidence? Perspectives on Psychological Science, 7, 528530.Google Scholar
Snijders, T.A., & Bosker, R.J. (2012). Multilevel analysis (2nd ed.). London, UK: Sage.Google Scholar

Further reading

Grimm, K.J., Zhang, Z., Hamagami, F., & Mazzocco, M.M. (2013). Modeling nonlinear change via latent change and latent acceleration frameworks: Examining velocity and acceleration of growth trajectories. Multivariate Behavioral Research, 48, 117143.Google Scholar
Hoyle, R.H. (2012). Handbook of structural equation modeling. New York, NY: Guilford Press.Google Scholar
Laursen, B., Little, T., & Card, N. (2011). Handbook of developmental research methods. New York, NY: Guilford Press.Google Scholar

References

Bollen, K.A. (1989). Structural equations with latent variables. New York, NY: Wiley.Google Scholar
Bollen, K.A., & Curran, P.J. (2006). Latent curve analysis: A structural equation perspective. Hoboken, NJ: Wiley.Google Scholar
Collins, L.M., & Sayer, A.G. (2001). New methods for the analysis of change. Washington, DC: American Psychological Association Press.Google Scholar
Grimm, K.J., Ram, N., & Hamagami, F. (2011). Nonlinear growth curves in developmental research. Child Development, 82, 13571371.Google Scholar
Kline, R.B. (2011). Principles and practice of structural equation modeling. New York, NY: Guilford Press.Google Scholar
Little, T.D. (2013). Longitudinal structural equation modeling. New York, NY: Guilford Press.Google Scholar
Loehlin, J.C. (2004). Latent variable models: An introduction to factor, path, and structural analysis. Mahwah, NJ: Erlbaum.Google Scholar
McArdle, J.J. (2001). A latent difference score approach to longitudinal dynamic structural analysis. In Cudeck, R., du Toit, S., & Sorbom, D. (Eds.), Structural equation modeling: Present and future (pp. 342380). Lincolnwood, IL: Scientific Software International.Google Scholar
McArdle, J.J., & Grimm, K.J. (2010). An empirical example of change analysis by linking longitudinal item response data from multiple tests. In von Davier, A. (Ed.), Statistical models for test equating, scaling, and linking (pp. 7188). New York, NY: Springer Science + Business Media.Google Scholar
McArdle, J.J., Grimm, K.J., Hamagami, F., Bowles, R.P., & Meredith, W. (2009). Modeling lifespan growth curves of cognition using longitudinal data with multiple samples and changing scales of measurement. Psychological Methods, 14, 126149.Google Scholar
McArdle, J.J., & Hamagami, F. (2001). Linear dynamic analyses of incomplete longitudinal data. In Collins, L. & Sayer, A. (Eds.), New methods for the analysis of change (pp. 137176). Washington, DC: American Psychological Association Press.Google Scholar
McArdle, J.J., & Nesselroade, J.R. (2014). Longitudinal data analysis using structural equation models. Washington, DC: American Psychological Association Press.Google Scholar
Meredith, W., & Tisak, J. (1990). Latent curve analysis. Psychometrika, 55, 107122.Google Scholar
Singer, J.D., & Willett, J.B. (2003). Applied longitudinal data analysis: Modeling change and event occurrence. New York, NY: Oxford University Press.Google Scholar

Further reading

Box, G., Jenkins, G.M., & Reinsel, G.C. (2013). Time series analysis: Forecasting and control (4th ed.). New York, NY: Wiley.Google Scholar
Chow, S.-M., Ferrer, E., & Hsieh, F. (Eds.) (2012). Statistical methods for modeling human dynamics: An interdisciplinary dialogue. London, UK: Taylor & Francis.Google Scholar
Shumway, R.H., & Stoffer, D.S. (2013). Time series analysis and its applications (3rd ed.). New York, NY: Springer.Google Scholar
Valsiner, J., Molenaar, P.C.M., Lyra, M.C.D.P., & Chaudhary, N. (Eds.) (2009). Dynamic process methodology in the social and developmental sciences. New York, NY: Springer.Google Scholar

References

Boker, S.M., & Laurenceau, J.P. (2005). Dynamical systems modeling: An application to the regulation of intimacy and disclosure in marriage. In Walls, T.A. & Schafer, J.L. (Eds.), Models for intensive longitudinal data (pp. 195218). Oxford, UK: Oxford University Press.Google Scholar
Boker, S.M., & Wenger, M.J. (Eds.) (2012). Data analytic techniques for dynamical systems. New York, NY: Psychology Press.Google Scholar
Brick, T.R., & Boker, S.M. (2011). Correlational methods for analysis of dance movements. Dance Research, 29 (supplement), 283304.Google Scholar
Cattell, R.B. (1952). The three basic factor-analytic research designs – their interrelations and derivatives. Psychological Bulletin, 49, 499–520.Google Scholar
Chow, S.-M., Ferrer, E., & Nesselroade, J.R. (2007). An unscented Kalman filter approach to the estimation of nonlinear dynamical systems models. Multivariate Behavioral Research, 42, 283321.Google Scholar
Chow, S.M., Ram, N., Boker, S.M., Fujita, F., & Clore, G. (2005). Emotion as a thermostat: Representing emotion regulation using a damped oscillator model. Emotion, 5, 208.Google Scholar
Chow, S.-M., & Zhang, G. (2008). Continuous-time modelling of irregularly spaced panel data using a cubic spline model. Statistica Neerlandica, 62, 131154.Google Scholar
Chow, S.-M., & Zhang, G. (2008). Continuous-time modelling of irregularly spaced panel data using a cubic spline model. Statistica Neerlandica, 62, 131154.Google Scholar
Gu, F., Preacher, K.J., Wu, W., & Yung, Y.-F. (2014). A computationally efficient state space approach to estimating multilevel regression models and multilevel confirmatory factor models. Multivariate Behavioral Research, 49, 119129.Google Scholar
Jorna, P.G.A.M. (1992). Spectral analysis of heart rate and psychological state: A review of its validity as a workload index. Biological Psychology, 34, 237257.Google Scholar
Molenaar, P.C.M. (2004). A manifesto on psychology as ideographic science: Bringing the person back into science psychology, this time forever. Measurement, 2, 201218.Google Scholar
Molenaar, P.C.M., Sinclair, K.O., Rovine, M.J., Ram, N., & Corneal, S.E. (2009). Analyzing developmental processes on an individual level using nonstationary time series modeling. Developmental Psychology, 45, 260271.Google Scholar
Visser, I., Raijmakers, M.E., & Molenaar, P.C. (2002). Fitting hidden Markov models to psychological data. Scientific Programming, 10, 185199.Google Scholar
Voelkle, M.C., Oud, J.H.L., von Oertzen, T., & Lindenberger, U. (2012). Maximum likelihood dynamic factor modeling for arbitrary n and t using SEM. Structural Equation Modeling: A Multidisciplinary Journal, 19, 329350.Google Scholar

Further reading

Harcourt, D., & Sargent, J. (2012). Doing ethical research with children. Maidenhead, UK: Open University Press.Google Scholar

References

Alderson, P., & Morrow, V. (2011). The ethics of research with children and young people. London, UK: Sage Publications.Google Scholar
Beck, U. (1998). World risk society. Cambridge, UK: Polity Press.Google Scholar
Campbell, A. (2008). For their own good: Recruiting children for research. Childhood, 15, 3049.Google Scholar
Clavering, E., & McLaughlin, J. (2010). Children’s participation in health research: From objects to agents? Child: Care, Health & Development, 36, 603611.Google Scholar
Coyne, I. (2010). Accessing children as research participants: Examining the role of gatekeepers. Child: Care, Health and Development, 36, 452454.Google Scholar
Finkelhor, D., Jones, L., & Kopic, K. (2005). Why is child sexual abuse declining? A survey of state child protection administrators. Child Abuse & Neglect, 25, 11391158.Google Scholar
Graham, A., & Fitzgerald, R. (2010). Children’s participation in research: Some possibilities and constraints in the current Australian research environment. Journal of Sociology, 46, 133147.Google Scholar
Hill, M. (2005). Ethical considerations in researching children’s experiences. In Greene, S. & Hogan, D. (Eds.), Researching children’s experience (pp. 6168). London, UK: Sage Publications.Google Scholar
Houston, S., Spratt, T., & Devaney, J. (2011). Mandated prevention in child welfare: Considerations from a framework shaping ethical inquiry. Journal of Social Work, 10, 369390.Google Scholar
Hood, S., Mayall, B., & Oliver, S. (1999). Critical issues in social research: Power and prejudice. Buckingham, UK: Open University Press.Google Scholar
Powell, M.A., Fitzgerald, R., Taylor, N.J., & Graham, A. (2012). International literature review: Ethical issues in undertaking research with children and young people (Literature review for the Childwatch International Research Network). Lismore, NZ: Southern Cross University, Centre for Children and Young People/Dunedin: University of Otago, Centre for Research on Children and Families.Google Scholar
Prout, A., & James, A. (1990). A new paradigm for the sociology of childhood? Provenance, promise and problems. In James, A. & Prout, A. (Eds.), Constructing and reconstructing childhood: New directions in the sociological study of childhood (pp. 734). London, UK: Falmer Press.Google Scholar
Spratt, T. (2012). Why multiples matter: Reconceptualising the population referred to child and family social workers. British Journal of Social Work, 42, 15741591.Google Scholar

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