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W. Adamowicz , D. Bunch , T. Cameron , B. Dellaert , M. Hanneman , M. Keane , J. Louviere , R. Meyer , T. Steenburgh and J. Swait (2008), ‘Behavioural frontiers in choice modelling’, Marketing Letters, 19: 215–228.
G. M. Allenby and P. E. Rossi (1998), ‘Marketing models of consumer heterogeneity’, Journal of Econometrics, 89(1–2): 57–78.
D. A. Anderson and J. Wiley (1992), ‘Efficient choice set designs for estimating cross effects models’, Marketing Letters, 3(4): 357–370.
N. H. Anderson (1981), Foundations of Information Integration Theory, New York: Academic Press.
M. Bech (2003), ‘Politicians’ and hospital managers’ trade-offs in the choice of reimbursement scheme: a discrete choice experiment’, Health Policy, 66(3): 261–275.
M. Bliemer , J. Rose and S. Hess (2008), ‘Approximation of Bayesian efficiency in experimental choice designs’, Journal of Choice Modelling, 1(1): 98–127.
R. A. Bradley and M. E. Terry (1952), ‘Rank analysis of incomplete block designs: I. The method of paired comparisons’, Biometrika, 39: 324–345.
E. Brunswick (1955), ‘Representative design and probabilistic theory in a functional psychology’, Psychological Review, 62: 193–217.
L. Burgess and A. Street (2005), ‘Optimal designs for choice experiments with asymmetric attributes’, Journal of Statistical Planning and Inference, 134(1): 288–301.
L. Burgess , D. Street , R. Viney and J. J. Louviere (2006), ‘Design of Choice Experiments in Health Economics’, in A. M. Jones (ed.), The Elgar Companion to Health Economics, Cheltenham, UK: Edward Elgar: 415–426.
J. Cairns and M. van der Pol (2004), ‘Repeated follow-up as a method for reducing non-trading behaviour in discrete choice experiments’, Social Science and Medicine, 58(11): 2211–2218.
F. Carlsson and P. Martinsson (2003), ‘Design techniques for stated preference methods in health economics’, Health Economics, 12: 281–294.
J. Coast and S. Horrocks (2007), ‘Developing attributes and levels for discrete choice experiments using qualitative methods’, Journal of Health Services and Research Policy, 12(1): 25–30.
J. R. DeShazo and G. Fermo (2002), ‘Designing choice sets for stated preference methods: the effects of complexity on choice consistency’, Journal of Environmental Economics and Management, 44: 123–143.
T. Erdem and M. Keane (1996), ‘Decision-making under uncertainty: capturing dynamic brand choice processes in turbulent consumer goods markets’, Marking Science, 15(1): 1–20.
T. Flynn , J. Louviere , T. Peters and J. Coast (2007), ‘Best–worst scaling: what it can do for health care and how to do it’, Journal of Health Economics, 26: 171–189.
P. Green and V. Rao (1971), ‘Conjoint measurement for quantifying judgement data’, Journal of Marketing Research, 8: 355–363.
W. H. Greene , D. A. Hensher and J. Rose (2006), ‘Accounting for heterogeneity in the variance of unobserved effects in mixed logit models’, Transportation Research Part B: Methodological, 40(1): 75–92.
D. Gyrd-Hansen (2004), ‘Investigating the social value of health changes’, Journal of Health Economics, 23(6): 1101–1116.
Z. Hakim and D. S. Pathak (1999), ‘Modelling the EuroQol data: a comparison of discrete choice conjoint and conditional preference modelling', Health Economics, 8(2): 103–116.
J. Hall , D. G. Fiebig , M. T. King , I. Hossain and J. J. Louviere (2006), ‘What influences participation in genetic carrier testing? Results from a discrete choice experiment’, Journal of Health Economics, 25(3): 520–537.
J. Hall , P. Kenny , M. King , J. Louviere , R. Viney and A. Yeoh (2002), ‘Using stated preference discrete choice modelling to evaluate the introduction of Varicella vaccination’, Health Economics, 11: 457–465.
A. R. Hole (2008), ‘Modelling heterogeneity in patients’ preferences for the attributes of a general practitioner appointment’, Health Economics, 27: 1078–1094.
J. Huber and K. Zwerina (1996), ‘The importance of utility balance in efficient choice designs’, Journal of Marketing Research, 33: 307–317.
T. Islam , J. J. Louviere and P. F. Burke (2007), ‘Modeling the effects of including/excluding attributes in choice experiment on systematic and random components’, International Journal of Research in Marketing, 24: 289–300.
S. Jan , G. Mooney , M. Ryan , K. Bruggemann and K. Alexander (2000), ‘The use of conjoint analysis to elicit community preferences in public health research: a case study of hospital services in South Australia’, Australian and New Zealand Journal of Public Health, 24: 64–70.
F. R. Johnson , M. R. Banzhaf and W. H. Desvousges (2000), ‘Willingness to pay for improved respiratory and cardiovascular health: a multiple-format stated preference approach’, Health Economics, 9(4): 295–317.
W. A. Kamakura and G. R. Russell (1989), ‘A probabilistic choice model for market segmentation and elasticity structure’, Journal of Marketing Research, 26(4): 379–390.
B. Kanninen (2002), ‘Optimal designs for multinomial choice experiments’, Journal of Marketing Research, 39: 214–227.
M. P. Keane and K. I. Wolpin (1994), ‘The solution and estimation of discrete choice dynamic programming models by simulation and interpolation: Monte Carlo evidence’, The Review of Economics Statistics, 76(4): 648–672.
M. G. Kendall and B. B. Smith (1940), ‘On the method of paired comparisons’, Biometrika, 31: 324–345.
M. T. King , J. Hall , E. Lancsar , D. Fiebig , I. Hossain , J. Louviere , H. K. Reddel and C. R. Jenkins (2007), ‘Patient preferences for managing asthma: results from a discrete choice experiment’, Health Economics, 16(7): 703–717.
T. Kjaer and D. Gyrd-Hansen (2008), ‘Preference heterogeneity and choice of cardiac rehabilitation program: results from a discrete choice experiment’, Health Policy, 85: 124–132.
E. Lancsar and J. Louviere (2006), ‘Deleting “irrational” responses from discrete choice experiments: a case of investigating or imposing preferences?’, Health Economics, 15(8): 797–811.
E. Lancsar and J. Louviere (2008a), ‘Conducting discrete choice experiments to inform healthcare decision making: a user’s guide’, Pharmacoeconomics, 26(8): 661–677.
E. Lancsar , J. Louviere and T. Flynn (2007a), ‘Several methods to investigate relative attribute impact in stated preference experiments’, Social Science and Medicine, 64(8): 1738–1753.
E. Lancsar and E. Savage (2004a), ‘Deriving welfare measures from discrete choice experiments: inconsistency between current methods and random utility and welfare theory, Health Economics, 13(9): 901–907.
E. Lancsar and E. Savage (2004b), ‘Deriving welfare measures from discrete choice experiments: a response to Ryan and Santos Silva’, Health Economics Letters, 13(9): 919–924.
E. J. Lancsar , J. P. Hall , M. King , P. Kenny , J. J. Louviere , D. G. Fiebig , I. Hossain , F. C. Thien , H. K. Reddel and C. R. Jenkins (2007b), ‘Using discrete choice experiments to investigate subject preferences for preventive asthma medication’, Respirology, 12(1): 127–136.
A. J. Lloyd (2003), ‘Threats to the estimation of benefit: are preference elicitation methods accurate?’, Health Economics, 12: 393–402.
J. Louviere , T. Islam , N. Wasi , D. Street and L. Burgess (2008), ‘Designing discrete choice experiments: do optimal designs come at a price?’ Journal of Consumer Research, 35: 360–376.
J. Louviere , A. Street , L. Burgess , N. Wasi , T. Islam and A. A. J. Marley (2008b), ‘Modeling the choices of individual decision-makers by combining efficient choice experiment designs with extra preference information’, The Journal of Choice Modelling, 1(1): 128–163.
J. Louviere and G. Woodworth (1983), ‘Design and analysis of simulated consumer choice or allocation experiments: an approach based on aggregated data’, Journal of Marketing Research, 20: 350–367.
T. Maddala , K. Phillips and F. R. Johnson (2003), ‘An experiment on simplifying conjoint analysis designs for measuring preferences’, Health Economics, 12: 1035–1047.
T. Mark and J. Swait (2004), ‘Using stated preference and revealed preference modelling to evaluate prescribing decisions’, Health Economics, 13(6): 563–573.
A. Marley and J. Louviere (2005), ‘Some probabilistic models of best, worst, and best–worst choices’, Journal of Mathematical Psychology, 49(6): 464–480.
A. A. J. Marley , T. Flynn and J. J. Louviere (2008), ‘Probabilistic models of set-dependent and attribute-level best–worst choice’, Journal of Mathematical Psychology, 52: 281–296.
E. McIntosh (2006), ‘Using discrete choice experiments within a cost–benefit analysis framework: some considerations’, Pharmacoeconomics, 24(9): 855–868.
C. Propper (1990), ‘Contingent valuation of time spent on NHS waiting lists’, Economic Journal, 100: 193–199.
D. Revelt and K. Train (1998), ‘Mixed logit with repeated choices of appliance efficiency levels’, Review of Economic Statistics, 80(4): 647–657.
D. Ruta , C. Mitton , A. Bate and C. Donaldson (2005), ‘Programme budgetting and marginal analysis (PBMA): bridging the divide between doctors and managers’, British Medical Journal, 330: 1501–1503.
M. Ryan (1999), ‘Using conjoint analysis to take account of patient preferences and go beyond health outcomes: an application to in vitro fertilisation’, Social Science and Medicine, 48(4): 535–546.
M. Ryan , K. Gerard and M. Amaya-Amaya (2008), Using Discrete Choice Experiments to Value Helath and Health Care, Dordrecht: Springer.
M. Ryan and J. Hughes (1997), ‘Using conjoint analysis to assess women’s preferences for miscarriage management’, Health Economics, 6(3): 261–273.
M. Ryan , A. Netten , D. Skatun and P. Smith (2006), ‘Using discrete choice experiments to estimate a preference-based measure of outcome: an application to social care for older people’, Journal of Health Economics, 25(5): 927–944.
M. Ryan and D. Skatun (2004), ‘Modelling non-demanders in choice experiments’, Health Economics, 13(4): 397–402.
A. Scott (2001), ‘Eliciting GPs’ preferences for pecuniary and non-pecuniary job characteristics’, Journal of Health Economics, 20: 329–347.
D. A. Street and L. Burgess (2004), ‘Optimal and near-optimal pairs for the estimation of effects in 2-level choice experiments’, Journal of Statistical Planning and Inference, 118: 185–199.
D. A. Street and L. Burgess (2007), The Construction of Optimal Stated Choice Experiments: Theory and Methods, Hoboken, NJ: Wiley.
D. A. Street , L. Burgess and J. J. Louviere (2005), ‘Quick and easy choice sets: constructing optimal and nearly optimal stated choice experiments’, International Journal of Research in Marketing, 22(4): 459–470.
D. J. Street , L. Burgess , R. Viney and J. J. Louviere (2008), ‘Designing Discrete Choice Experiments for Health Care’, in M. Ryan , K. Gerard and M. Amaya-Amaya (eds), Using Discrete Choice Experiments to Value Health and Health Care, Dordrecht, The Netherlands: Springer: 47–72.
J. Swait (2001), ‘A non-compensatory choice model incorporating attribute cutoffs’, Transportation Research. Part B: Methodological, 35(10): 903–928.
J. Swait and W. Adamowicz (2001), ‘Choice environment, market complexity, and consumer behavior: a theoretical and empirical approach for incorporating decision complexity into models of consumer choice’, Organizational Behavior and Human Decision Processes, 86(2): 141–167.
L. Thurstone (1927), ‘A law of comparative judgement’, Psychological Review, 34: 273–286.
M. van der Pol and J. Cairns (2001), ‘Estimating time preference for health using discrete choice experiments’, Social Science and Medicine, 52: 1459–1470.
R. Viney , E. Lancsar and J. Louviere (2002), ‘Discrete choice experiments to measure consumer preferences for health and healthcare’, Expert Review of Pharmacoeconomics and Outcomes Research, 2(4): 319–326.
R. Viney , E. Savage and J. Louviere (2005), ‘Empirical investigation of experimental design properties of discrete choice experiments in health care’, Health Economics, 14(4): 349–362.
A. J. Wells (1991), ‘Optimal presentation orders for the method of paired comparisons’, British Journal of Mathematical and Statistical Psychology, 44(1): 181–193.