Hostname: page-component-7dd5485656-s6l46 Total loading time: 0 Render date: 2025-10-31T12:07:06.409Z Has data issue: false hasContentIssue false
  • English
  • Français

Examining income dynamics and externalizing and internalizing trajectories through a developmental psychopathology lens: A nationally representative study

Published online by Cambridge University Press:  24 February 2020

Portia Miller Open the ORCID record for Portia Miller [Opens in a new window] ,
Laura Betancur ,
Kendra Whitfield  and
Elizabeth Votruba-Drzal
Portia Miller*
Affiliation:
Learning Research and Development Center, University of Pittsburgh, Pittsburgh, PA, USA
Laura Betancur
Affiliation:
Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
Kendra Whitfield
Affiliation:
Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
Elizabeth Votruba-Drzal
Affiliation:
Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
*
Author for correspondence: Portia Miller, Learning Research and Development Center, University of Pittsburgh, 3939 O'Hara Street, Pittsburgh, PA 15213; E-mail: plm11@pitt.edu.
Get access Rights & Permissions [Opens in a new window]

Abstract

Prior research has documented elevations in levels of internalizing and externalizing behaviors among children in lower income families in comparison to more advantaged peers. However, most studies focus on behavior problems at a single point in time or within a short developmental period. Associations between income dynamics and developmental trajectories of behavior problems over time are less understood. To address this, the current study uses data from the National Longitudinal Study of Youth (N = 7,476; 50.8% male) to examine how income dynamics (annual income and income volatility) across three distinct developmental periods from early childhood to early adolescence relate to trajectories of externalizing and internalizing problems. Group-based mixture modeling revealed a five-group trajectory model for externalizing behavior and a four-group trajectory model for internalizing behavior. Higher cumulative annual income predicted greater likelihood of belonging to the low-stable group compared to the other, more problematic groups for both externalizing and internalizing trajectories. In addition, income losses predicted higher risk of membership in any group other than the low-stable group for internalizing and externalizing behavior. Developmental period-specific income dynamics, though not as consistent as cumulative dynamics, also predicted trajectory group membership.

Keywords

externalizingincomeinternalizingtrajectory modeling

Information

Type
Regular Articles
Information
Development and Psychopathology , Volume 33 , Issue 1 , February 2021 , pp. 1 - 17
Check for updates
Copyright
Copyright © Cambridge University Press 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Aaronson, D., & Mazumder, B. (2008). Intergenerational economic mobility in the United States, 1940 to 2000. Journal of Human Resources, 43, 139–172.CrossRefGoogle Scholar
Akee, R. K., Copeland, W. E., Keeler, G., Angold, A., & Costello, E. J. (2010). Parents' incomes and children's outcomes: A quasi-experiment using transfer payments from casino profits. American Economic Journal: Applied Economics, 2, 86–115.Google Scholar
Asparouhov, T., & Muthén, B. (2013). Auxiliary variables in mixture modeling: 3-step approaches using Mplus. Mplus Web Notes, 15. Retrieved from https://statmodel.com/examples/webnotes/AuxMixture_submitted_corrected_webnoteGoogle Scholar
Becker, G. S. (1991). A treatise on the family. Cambridge, MA: Harvard University Press.Google Scholar
Blair, C., & Raver, C. C. (2012). Child development in the context of adversity. American Psychologist, 67, 309–318. doi:10.1037/a0027493CrossRefGoogle ScholarPubMed
Blair, C., & Raver, C. C. (2016). Poverty, stress, and brain development: New directions for prevention and intervention. Academic Pediatrics, 16, S30–S36.CrossRefGoogle ScholarPubMed
Blau, D. M. (1999). The effect of income on child development. Review of Economics and Statistics, 81, 261–276. doi:10.1162/003465399558067CrossRefGoogle Scholar
Bongers, I. L., Koot, H. M., van der Ende, J., & Verhulst, F. C. (2008). Predicting young adult social functioning from developmental trajectories of externalizing behaviour. Psychological Medicine, 38, 989–999.CrossRefGoogle ScholarPubMed
Brody, G. H., Flor, D. L., & Gibson, N. M. (1999). Linking maternal efficacy beliefs, developmental goals, parenting practices, and child competence in rural single-parent African American families. Child Development, 70, 1197–1208.CrossRefGoogle ScholarPubMed
Broidy, L. M., Nagin, D. S., Tremblay, R. E., Bates, J. E., Brame, B., Dodge, K. A., & Lynam, D. R. (2003). Developmental trajectories of childhood disruptive behaviors and adolescent delinquency: A six-site, cross-national study. Developmental Psychology, 39, 222.CrossRefGoogle ScholarPubMed
Brotman, L. M., O'Neal, C. R., Huang, K.-Y., Gouley, K. K., Rosenfelt, A., & Shrout, P. E. (2009). An experimental test of parenting practices as a mediator of early childhood physical aggression. Journal of Child Psychology and Psychiatry, 50, 235–245. doi:10.1111/j.1469-7610.2008.01929.xCrossRefGoogle ScholarPubMed
Campbell, S. B., Spieker, S., Burchinal, M., Poe, M. D., & the National Institute of Child Health and Human Development Early Child Care Research Network (2006). Trajectories of aggression from toddlerhood to age 9 predict academic and social functioning through age 12. Journal of Child Psychology and Psychiatry, 47, 791–800.CrossRefGoogle ScholarPubMed
Carter, A. S., Wagmiller, R. J., Gray, S. A. O., McCarthy, K. J., Horwitz, S. M., & Briggs-Gowan, M. J. (2010). Prevalence of DSM-IV disorder in a representative, healthy birth cohort at school entry: Sociodemographic risks and social adaptation. Journal of the American Academy of Child & Adolescent Psychiatry, 49, 686–698. doi:10.1016/j.jaac.2010.03.018Google Scholar
Castelao, C. F., & Kröner-Herwig, B. (2013). Different trajectories of depressive symptoms in children and adolescents: Predictors and differences in girls and boys. Journal of Youth and Adolescence, 42, 1169–1182.CrossRefGoogle Scholar
Center for Human Resource Research (CHRR). (2002). NLSY79 child & young adult data user's guide: A guide to the 1986–2000 child data, 1994–2000 young adult data. Columbus, OH: Ohio State University Press.Google Scholar
Choe, D. E., Olson, S. L., & Sameroff, A. J. (2013). Effects of early maternal distress and parenting on the development of children's self-regulation and externalizing behavior. Development and Psychopathology, 25, 437–453. doi:10.1017/S0954579412001162Google ScholarPubMed
Clark-Kauffman, E., Duncan, G. J., & Morris, P. (2003). How welfare policies affect child and adolescent achievement. American Economic Review, 93, 299–303.CrossRefGoogle Scholar
Conger, R. D., Conger, K. J., Elder, G. H., Lorenz, F. O., Simons, R. L., & Whitbeck, L. B. (1992). A family process model of economic hardship and adjustment of early adolescent boys. Child Development, 63, 526–541. doi:10.2307/1131344CrossRefGoogle ScholarPubMed
Conger, R. D., Conger, K. J., Matthews, L. S., & Elder, G. H. (1999). Pathways of economic influence on adolescent adjustment. American Journal of Community Psychology, 27, 519–541. doi:10.1023/A:1022133228206CrossRefGoogle ScholarPubMed
Conger, R. D., & Conger, K. J. (2002). Midwestern families: Selected findings from the first decade of a prospective, longitudinal study. Journal of Marriage and Family, 64, 361–373.CrossRefGoogle Scholar
Conger, R. D., & Elder, G. H. (1994). Families in troubled times: Adapting to change in rural America. Social Institutions and Social Change Series. Hawthorne, NY: Routledge.Google Scholar
Costello, E. J., Compton, S. N., Keeler, G., & Angold, A. (2003). Relationships between poverty and psychopathology: A natural experiment. Journal of the American Medical Association, 290, 2023–2029.CrossRefGoogle ScholarPubMed
Costello, E. J., Egger, H. L., & Angold, A. (2005). The developmental epidemiology of anxiety disorders: Phenomenology, prevalence, and comorbidity. Child and Adolescent Psychiatric Clinics of North America, 14, 631–648.CrossRefGoogle ScholarPubMed
Costello, E. J., Erkanli, A., Copeland, W., & Angold, A. (2010). Association of family income supplements in adolescence with development of psychiatric and substance use disorders in adulthood among an American Indian population. Journal of the American Medical Association, 303, 1954–1960. doi:10.1001/jama.2010.621CrossRefGoogle ScholarPubMed
Davis, S., Votruba-Drzal, E., & Silk, J. S. (2015). Trajectories of internalizing symptoms from early childhood to adolescence: Associations with temperament and parenting. Social Development, 24, 501–520.CrossRefGoogle Scholar
Dearing, E., McCartney, K., & Taylor, B. A. (2006). Within-child associations between family income and externalizing and internalizing problems. Developmental Psychology, 42, 237–252. doi:10.1037/0012-1649.42.2.237CrossRefGoogle ScholarPubMed
Dekker, M. C., Ferdinand, R. F., Van Lang, N. D., Bongers, I. L., van der Ende, J., & Verhulst, F. C. (2007). Developmental trajectories of depressive symptoms from early childhood to late adolescence: Gender differences and adult outcome. Journal of Child Psychology and Psychiatry, 48, 657–666.CrossRefGoogle ScholarPubMed
Dekovic, M., Buist, K. L., & Reitz, E. (2004). Stability and changes in problem behavior during adolescence: Latent growth analysis. Journal of Youth and Adolescence, 33, 1–12. doi:10.1023/A:1027305312204CrossRefGoogle Scholar
D'Onofrio, B. M., Goodnight, J. A., Hulle, C. A. V., Rodgers, J. L., Rathouz, P. J., Waldman, I. D., & Lahey, B. B. (2009). Maternal age at childbirth and offspring disruptive behaviors: Testing the causal hypothesis. Journal of Child Psychology and Psychiatry, 50, 1018–1028. doi:10.1111/j.1469-7610.2009.02068.xCrossRefGoogle ScholarPubMed
National Institute of Child Health and Human Development Early Child Care Research Network, & Duncan, G. J. (2003). Modeling the impacts of child care quality on children's preschool cognitive development. Child Development, 74, 1454 –1475.Google ScholarPubMed
Duncan, G. J., & Brooks-Gunn, J. (Eds.). (1997). Consequences of growing up poor (pp. 596–610). New York: Sage.Google Scholar
Duncan, G. J., Engel, M., Claessens, A., & Dowsett, C. J. (2014). Replication and robustness in developmental research. Developmental Psychology, 50, 2417–2425.CrossRefGoogle ScholarPubMed
Duncan, G. J., Kalil, A., & Ziol-Guest, K. (2008). Economic costs of early childhood poverty (Issue Paper 4). Washington, DC: Partnership for America's Economic Success.Google Scholar
Duncan, G. J., Magnuson, K., & Votruba-Drzal, E. (2017). Moving beyond correlations in assessing the consequences of poverty. Annual Review of Psychology, 68, 413–434.CrossRefGoogle Scholar
Duncan, G. J., Ziol-Guest, K. M., & Kalil, A. (2010). Early-childhood poverty and adult attainment, behavior, and health. Child Development, 81, 306–325.CrossRefGoogle Scholar
Dynan, K. E., Elmendorf, D. W., & Sichel, D. E. (2007). The evolution of household income volatility. Federal Reserve Board Finance and Economics Discussion Series 2007-61. Washington, DC: Federal Reserve.Google Scholar
Eamon, M. K. (2000). Structural model of the effects of poverty on externalizing and internalizing behaviors of four- to five-year-old children. Social Work Research, 24, 143–154. doi:10.1093/swr/24.3.143CrossRefGoogle Scholar
Elder, G. H. Jr. (1974). Children of the great depression. Chicago, IL: University of Chicago Press.Google Scholar
Evans, G. W., & English, K. (2002). The environment of poverty: Multiple stressor exposure, psychophysiological stress, and socioemotional adjustment. Child Development, 73, 1238–1248.CrossRefGoogle ScholarPubMed
Evans, G. W., Gonnella, C., Marcynyszyn, L. A., Gentile, L., & Salpekar, N. (2005). The role of chaos in poverty and children's socioemotional adjustment. Psychological Science, 16, 560–565. doi:10.1111/j.0956-7976.2005.01575.xCrossRefGoogle ScholarPubMed
Fanti, K. A., & Henrich, C. C. (2010). Trajectories of pure and co-occurring internalizing and externalizing problems from age 2 to age 12: Findings from the National Institute of Child Health and Human Development Study of Early Child Care. Developmental Psychology, 46, 1159.CrossRefGoogle ScholarPubMed
Feng, X., Shaw, D. S., & Silk, J. S. (2008). Developmental trajectories of anxiety symptoms among boys across early and middle childhood. Journal of Abnormal Psychology, 117, 32.CrossRefGoogle ScholarPubMed
Flouri, E., Midouhas, E., & Joshi, H. (2014). Family poverty and trajectories of children's emotional and behavioural problems: The moderating roles of self-regulation and verbal cognitive ability. Journal of Abnormal Child Psychology, 42, 1043–1056. doi:10.1007/s10802-013-9848-3CrossRefGoogle ScholarPubMed
Gennetian, L. A., & Miller, C. (2002). Children and welfare reform: A view from an experimental welfare program in Minnesota. Child Development, 73, 601–620.CrossRefGoogle ScholarPubMed
Gennetian, L. A., Rodrigues, C., Hill, H. D., & Morris, P. A. (2018). Income level and volatility by children's race and Hispanic ethnicity. Journal of Marriage and Family, 81, 204–229. doi:10.1111/jomf.12529CrossRefGoogle Scholar
Gershoff, E. T., Aber, J. L., Raver, C. C., & Lennon, M. C. (2007). Income is not enough: Incorporating material hardship into models of income associations with parenting and child development. Child Development, 78, 70–95.CrossRefGoogle Scholar
Gutman, L. M., Joshi, H., Parsonage, M., & Schoon, I. (2018). Gender-specific trajectories of conduct problems from ages 3 to 11. Journal of Abnormal Child Psychology, 46, 1467–1480.CrossRefGoogle ScholarPubMed
Hankin, B. L., Abramson, L. Y., Moffitt, T. E., Silva, P. A., McGee, R., & Angell, K. E. (1998). Development of depression from preadolescence to young adulthood: Emerging gender differences in a 10-year longitudinal study. Journal of Abnormal Psychology, 107, 128.CrossRefGoogle Scholar
Hao, L., & Matsueda, R. L. (2006). Family dynamics through childhood: A sibling model of behavior problems. Social Science Research, 35, 500–524.CrossRefGoogle Scholar
Hardy, B. L. (2014). Childhood income volatility and adult outcomes. Demography, 51, 1641–1665. doi:10.1007/s13524-014-0329-2CrossRefGoogle ScholarPubMed
Harold, G. T., & Conger, R. (1997). Marital conflict and adolescent distress: The role of adolescent awareness. Child Development, 68, 333–350.Google ScholarPubMed
Hill, H. D., Morris, P., Gennetian, L. A., Wolf, S., & Tubbs, C. (2013). The consequences of income instability for children's well-being. Child Development Perspectives, 7, 85–90.CrossRefGoogle ScholarPubMed
Huston, A. C., Duncan, G. J., Granger, R., Bos, J., McLoyd, V., Mistry, R., … Ventura, A. (2001). Work-based antipoverty programs for parents can enhance the school performance and social behavior of children. Child Development, 72, 318.CrossRefGoogle ScholarPubMed
Jung, T., & Mickrama, K. A. S. (2007). An introduction to latent class growth analysis and growth mixture modeling. Social and Personality Psychology Compass, 2, 302–317.CrossRefGoogle Scholar
Korenman, S., Miller, J. E., & Sjaastad, J. E. (1995). Long-term poverty and child development in the United States: Results from the NLSY. Madison, WI: University of Wisconsin–Madison, Institute for Research on Poverty.Google Scholar
Larsson, H., Chang, Z., D'Onofrio, B. M., & Lichtenstein, P. (2014). The heritability of clinically diagnosed attention deficit hyperactivity disorder across the lifespan. Psychological Medicine, 44, 2223–2229. doi:10.1017/S0033291713002493CrossRefGoogle ScholarPubMed
Lefebvre, P., & Merrigan, P. (1998). Family background, family income, maternal work and child development (CREFE Working Papers 78). University of Quebec at Montreal: CREFE.Google Scholar
Leve, L. D., Kim, H. K., & Pears, K. C. (2005). Childhood temperament and family environment as predictors of internalizing and externalizing trajectories from ages 5 to 17. Journal of Abnormal Child Psychology, 33, 505–520.CrossRefGoogle ScholarPubMed
Leventhal, T., & Brooks-Gunn, J. (2000). The neighborhoods they live in: The effects of neighborhood residence on child and adolescent outcomes. Psychological Bulletin, 126, 309.CrossRefGoogle ScholarPubMed
Linver, M. R., Brooks-Gunn, J., & Kohen, D. E. (2002). Family processes as pathways from income to young children's development. Developmental Psychology, 38, 719–734. doi:10.1037//0012-1649.38.5.719CrossRefGoogle ScholarPubMed
López-Romero, L., Romero, E., & Andershed, H. (2015). Conduct problems in childhood and adolescence: Developmental trajectories, predictors and outcomes in a six-year follow up. Child Psychiatry & Human Development, 46, 762–773.CrossRefGoogle Scholar
MacCallum, R. C., & Austin, J. T. (2000). Applications of structural equation modeling in psychological research. Annual Review of Psychology, 51, 201–226.CrossRefGoogle ScholarPubMed
Magnuson, K. A., & Votruba-Drzal, E. (2009). Enduring influences of childhood poverty. In Cancian, M. & Danziger, S. (Eds.), Changing poverty, changing policies (pp. 153–179). New York: Sage.Google Scholar
Mayer, S. E. (1997). What money can't buy: Family income and children's life chances. Cambridge, MA: Harvard University Press.Google Scholar
McKee, L., Roland, E., Coffelt, N., Olson, A. L., Forehand, R., Massari, C., … Zens, M. S. (2007). Harsh discipline and child problem behaviors: The roles of positive parenting and gender. Journal of Family Violence, 22, 187–196. doi:10.1007/s10896-007-9070-6CrossRefGoogle Scholar
McLoyd, V. C. (1990). The impact of economic hardship on Black families and children: Psychological distress, parenting, and socioemotional development. Child Development, 61, 311–346.CrossRefGoogle ScholarPubMed
McLoyd, V. C. (2019). How children and adolescents think about, make sense of, and respond to economic inequality: Why does it matter? Developmental Psychology, 53, 592.CrossRefGoogle Scholar
McLoyd, V. C., Kaplan, R., Purtell, K. M., Bagley, E., Hardaway, C. R., & Smalls, C. (2009). Poverty and socioeconomic disadvantage in adolescence. In Lerner, R. M. & Steinberg, L. (Eds.), Handbook of adolescent psychology (3rd ed., pp. 444–491). New York: Wiley.Google Scholar
Miller, P., & Votruba-Drzal, E. (2017). The role of family income dynamics in predicting trajectories of internalizing and externalizing problems. Journal of Abnormal Child Psychology, 45, 543–556. doi:10.1007/s10802-016-0181-5CrossRefGoogle ScholarPubMed
Miller, P., Whitfield, C., Betancur, C., & Votruba-Drzal, E. (2019). Income dynamics and the development of behavior problems from early childhood through the transition to adolescence. Unpublished manuscript.Google Scholar
Miner, J. L., & Clark-Stewart, K. A. (2008). Trajectories of externalizing behavior from age 2 to age 9: Relations with gender, temperament, ethnicity, parenting, and rater. Developmental Psychology, 44, 771–786.CrossRefGoogle ScholarPubMed
Mistry, R. S., Biesanz, J. C., Taylor, L. C., Burchinal, M., & Cox, M. J. (2004). Family income and its relation to preschool children's adjustment for families in the NICHD study of early child care. Developmental Psychology, 40, 727.CrossRefGoogle ScholarPubMed
Moffitt, T. E. (2017). Life-course-persistent versus adolescence-limited antisocial behavior. In McGee, T. R. & Mazorelle, P. (Eds.), Developmental and life-course criminological theories (pp. 75–103). London: Routledge.CrossRefGoogle Scholar
Morris, P. A., Hill, H. D., Gennetian, L. A., Rodrigues, C., & Wolf, S. (2015). Income volatility in US households with children: Another growing disparity between the rich and the poor? Madison, WI: University of Wisconsin–Madison, Institute for Research on Poverty.Google Scholar
Muthén, B. (2004). Latent variable analysis: Growth mixture modeling and related techniques for longitudinal data. In Kaplan, D. (Ed.), The Sage handbook of quantitative methodology for the social sciences (pp. 345–368). Newbury Park, CA: Sage.Google Scholar
Muthén, L. K., & Muthén, B. O. (1998–2017). Mplus user's guide (8th ed.). Los Angeles: Author.Google Scholar
Nagin, D., & Tremblay, R. E. (1999). Trajectories of boys' physical aggression, opposition, and hyperactivity on the path to physically violent and nonviolent juvenile delinquency. Child Development, 70, 1181–1196.CrossRefGoogle ScholarPubMed
Palacios-Barrios, E. E., & Hanson, J. L. (2019). Poverty and self-regulation: Connecting psychosocial processes, neurobiology, and the risk for psychopathology. Comprehensive Psychiatry, 90, 52–64.CrossRefGoogle ScholarPubMed
Petersen, I. T., Bates, J. E., Dodge, K. A., Lansford, J. E., & Pettit, G. S. (2015). Describing and predicting developmental profiles of externalizing problems from childhood to adulthood. Development and Psychopathology, 27, 791–818.CrossRefGoogle ScholarPubMed
Peterson, J. L., & Zill, N. (1986). Marital disruption, parent-child relationships, and behavior problems in children. Journal of Marriage and the Family, 48, 295–307.CrossRefGoogle Scholar
Phillips, D. A., & Shonkoff, J. P. (Eds.). (2000). From neurons to neighborhoods: The science of early childhood development. Washington, DC: National Academies Press.Google Scholar
Reef, J., Donker, A. G., VanMeurs, I., Verhulst, F. C., & van der Ende, J. (2011). Predicting adult violent delinquency: Gender differences regarding the role of childhood behaviour. European Journal of Criminology, 8, 187–197.CrossRefGoogle Scholar
Royston, P. (2005). Multiple imputation of missing values: Update. Stata Journal, 5, 188–201.CrossRefGoogle Scholar
Sameroff, A. J. (2014). A dialectic integration of development for the study of psychopathology. In Handbook of developmental psychopathology (pp. 25–43). Boston: Springer.CrossRefGoogle Scholar
Scaramella, L. V., Conger, R. D., & Simons, R. L. (1999). Parental protective influences and gender-specific increases in adolescent internalizing and externalizing problems. Journal of Research on Adolescence, 9, 111–141.CrossRefGoogle Scholar
Schaeffer, C. M., Petras, H., Ialongo, N., Masyn, K. E., Hubbard, S., Poduska, J., & Kellam, S. (2006). A comparison of girls' and boys' aggressive-disruptive behavior trajectories across elementary school: Prediction to young adult antisocial outcomes. Journal of Consulting and Clinical Psychology, 74, 500.CrossRefGoogle ScholarPubMed
Shaffer, D., Fisher, P., Dulcan, M. K., Davies, M., Piacentini, J., Schwab-Stone, M. E., & Canino, G. (1996). The NIMH Diagnostic Interview Schedule for Children Version 2.3 (DISC-2.3): Description, acceptability, prevalence rates, and performance in the MECA study. Journal of the American Academy of Child & Adolescent Psychiatry, 35, 865–877.CrossRefGoogle ScholarPubMed
Shaw, D. S., Gilliom, M., Ingoldsby, E. M., & Nagin, D. S. (2003). Trajectories leading to school-age conduct problems. Developmental Psychology, 39, 189.CrossRefGoogle ScholarPubMed
Shaw, D. S., Hyde, L. W., & Brennan, L. M. (2012). Early predictors of boys' antisocial trajectories. Development and Psychopathology, 24, 871–888.CrossRefGoogle ScholarPubMed
Steinberg, L. (2005). Cognitive and affective development in adolescence. Trends in Cognitive Sciences, 9, 69–74. doi:10.1016/j.tics.2004.12.005CrossRefGoogle ScholarPubMed
Steinberg, L. (2008). A social neuroscience perspective on adolescent risk-taking. Developmental Review, 28, 78–106. doi:10.1016/j.dr.2007.08.002CrossRefGoogle ScholarPubMed
Sterba, S. K. (2014). Fitting nonlinear latent growth curve models with individually varying time points. Structural Equation Modeling, 21, 630–647.CrossRefGoogle Scholar
Sterba, S. K., Prinstein, M. J., & Cox, M. J. (2007). Trajectories of internalizing problems across childhood: Heterogeneity, external validity, and gender differences. Development and Psychopathology, 19, 345–366.CrossRefGoogle ScholarPubMed
Timmermans, M., Van Lier, P. A., & Koot, H. M. (2008). Which forms of child/adolescent externalizing behaviors account for late adolescent risky sexual behavior and substance use? Journal of Child Psychology and Psychiatry, 49, 386–394.CrossRefGoogle ScholarPubMed
US Department of Labor Statistics (n.d.). Custom Weighting Program Documentation. Retrieved from https://www.nlsinfo.org/weights/custom-weighting-program-documentationGoogle Scholar
Volruba-Drzal, E. (2003). Income changes and cognitive stimulation in young children's home learning environments. Journal of Marriage and Family, 65, 341–355.CrossRefGoogle Scholar
Votruba-Drzal, E. (2006). Economic disparities in middle childhood development: Does income matter? Developmental Psychology, 42, 1154–1167. doi:10.1037/0012-1649.42.6.1154CrossRefGoogle ScholarPubMed
Wadsworth, M. E., Evans, G. W., Grant, K., Carter, J. S., & Duffy, S. (2016). Poverty and the development of psychopathology. In Cicchetti, D. (Ed.), Developmental psychopathology: Vol. 4. Risk, Resilience, and intervention (pp. 1–44). Hoboken, NJ: Wiley.Google Scholar
Yeung, W. J., Linver, M. R., & Brooks–Gunn, J. (2002). How money matters for young children's development: Parental investment and family processes. Child Development, 73, 1861–1879. doi:10.1111/1467-8624.t01-1-00511CrossRefGoogle ScholarPubMed
Zilanawala, A., & Pilkauskas, N. V. (2012). Material hardship and child socioemotional behaviors: Differences by types of hardship, timing, and duration. Children and Youth Services Review, 34, 814–825.CrossRefGoogle ScholarPubMed
Ziliak, J. P., Hardy, B., & Bollinger, C. (2011). Earnings volatility in America: Evidence from matched CPS. Labour Economics, 18, 742–775.CrossRefGoogle Scholar
Zill, N., & Peterson, J. L. (1986). Behavior Problems Index. Washington, DC: Child Trends.Google Scholar