Effects of simplifying choice tasks on estimates of taste heterogeneity in stated-choice surveys

Social Science and Medicine

Volumn 70, Issue 2, 2010, Pages 183-190

  Johnson, F Reed ^a   Ozdemir, Semra ^b   Phillips, Kathryn A ^c  

^a RTI HEALTH SOLUTIONS   (United States)

^b IL   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DESIGN; ESTIMATION METHOD; HETEROGENEITY; HUMAN IMMUNODEFICIENCY VIRUS; QUESTIONNAIRE SURVEY; WILLINGNESS TO PAY;

ARTICLE; CONTROLLED STUDY; DECISION MAKING; DIAGNOSTIC TEST; HUMAN IMMUNODEFICIENCY VIRUS INFECTION; MEASUREMENT ERROR; PATIENT COUNSELING; PRIVACY; UNITED STATES;

AIDS SERODIAGNOSIS; CHOICE BEHAVIOR; CONSUMER SATISFACTION; DATA COLLECTION; ETHNIC GROUPS; FINANCING, PERSONAL; HIV INFECTIONS; HOMOSEXUALITY, MALE; HUMANS; MALE; MODELS, THEORETICAL; SAN FRANCISCO; SOCIOECONOMIC FACTORS;

CALIFORNIA; NORTH AMERICA; SAN FRANCISCO; UNITED STATES;

EID: 71849105174     PISSN: 02779536     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.socscimed.2009.10.021     Document Type: Article

References (51)

1. Arentze T.A., Borgers A., Delmistro R., and Timmermans H. Transport stated choice responses: effects of task complexity, presentation format and literacy. Transport Research E 39 (2003) 229-244
2. Bennett J., and Adamowicz V. Some fundamentals of environmental choice modeling. In: Bennett J., and Blamey R. (Eds). The choice modeling approach to environmental valuation (2001), Edward Elgar, Cheltenham
3. Bhat C. Accommodating variations in responsiveness to level-of-service variables in travel mode choice modeling. Transportation Research Part A 32 7 (1998) 495-507
4. Bhat C. Incorporating observed and unobserved heterogeneity in urbanwork mode choice modeling. Transportation Science 34 2 (2000) 228-238
5. Bradley M.A., and Daly A.J. Use of the logit scaling approach to test rank-order and fatigue effects in stated preference data. Transportation 21 2 (1994) 167-184
6. Chernev A. The effect of common features on brand choice: moderating role of attribute importance. The Journal of Consumer Research 23 4 (1997) 304-311
7. Chernev A. Extremeness aversion and attribute-balance effects in choice. Journal of Consumer Research 31 (September 2004) 249-263
8. DeShazo J.R., and Fermo G. Designing choice sets for stated preference methods: the effects of complexity on choice consistency. Journal of Environmental Economics and Management 44 (2002) 123-143
9. Diener A., O'Brien B., and Gafni A. Health care contingent valuation studies: a review and classification of the literature. Health Economics 7 (1998) 313-326
10. GAUSS matrix language (2004), Aptech Systems, Inc, Maple Valley, WA
11. Green P.E., and Rao V.R. Conjoint measurement for quantifying judgmental data. Journal of Marketing Research 8 (1971) 355-363
12. Greene W.H. Econometric analysis (1993), Macmillan Publishing Company, New York
13. Greene W.H., Hensher D.A., and Rose J.M. Accounting for heterogeneity in the variance of unobserved effects in mixed logit models. Transportation Research Part B 40 1 (2006) 75-92
14. Hensher D.A., Rose J.M., and Greene W.H. Applied choice analysis: A primer (2005), Cambridge University Press, Cambridge, UK
15. Hensher D.A., Stopher P.R., and Louviere J.J. An exploratory analysis of the effect of numbers of choice sets in designed choice experiments: an airline choice application. Journal of Air Transport Management 7 (2001) 373-379
16. Hole, A. R. (2008). Modeling heterogeneity in patients' preferences for the attributes of a general practitioner appointment. Journal of Health Economics (in print).
17. Holmes T., and Adamowicz V. Attribute-based methods. In: Champ P., Boyle K.J., and Brown T. (Eds). A primer on nonmarket valuation (2003), Kluwer Academic Publishers, Netherlands
18. Huber, J. What we have learned from 20 years of conjoint research: when to use self-explicated, graded pairs, full profiles or choice experiments, 1997, Sawtooth Software Conference.
19. Huber J., and Train K. On the similarity of classical and bayesian estimates of individual mean partworths. Marketing Letters 12 3 (2001) 259-269
20. Huber J., and Zwerina K. The importance of utility balance in efficient choice designs. Journal of Marketing Research 33 2 (1996) 307-317
21. Islam T., Louviere J.J., and Burke P.F. Modeling the effects of including/excluding attributes in choice experiments on systematic and random components. International Journal of Research in Marketing 24 4 (2007) 289-300
22. Johnson E.J., and Meyer R.J. Compensatory models of non-compensatory choice processes: the effect of varying context. Journal of Consumer Research 11 (1984) 528-541
23. Johnson F.R., Banzhaf M.R., and Desvousges W.H. Willingness to pay for improved respiratory and cardiovascular health: a multiple-format, stated-preference approach. Health Economics 9 (2000) 295-317
24. Johnson F.R., Desvousges W.H., Ruby M.C., Stieb D., and Civita P.D. Eliciting stated health preferences: an application to willingness to pay for longevity. Medical Decision Making 18 (1998) S57-S67
25. Johnson F.R., Özdemir S., Mansfield C., Hass S., Miller D.W., Siegel C.A., et al. Crohn's disease patients' risk-benefit preferences: serious adverse event risks versus treatment efficacy. Gastroenterology 133 3 (2007) 769-779
26. Kanninen B. Optimal design for multinomial choice experiments. Journal of Marketing Research 39 (May 2002) 214-227
27. LIMDEP (2005), Econometric Software, Inc, Plainview, NY
28. Louviere J.J., and Hensher D.A. Using discrete choice models with experimental design data to forecast consumer demand for a unique cultural event. Journal of Consumer Research 10 (1983) 348-361
29. Louviere J.J., Hensher D.A., and Swait J.D. Stated choice methods: Analysis and application (2000), Cambridge University Press, Cambridge, UK
30. Maddala T., Phillips K.A., and Johnson F.R. An experiment on simplifying conjoint analysis exercises for measuring HIV testing preferences. Health Economics 12 12 (2003) 1035-1047
31. Mark T.L., and Swait J. Using stated preference modeling to forecast the effect of medication attributes on prescriptions of alcoholism medications. Value in Health 6 4 (2003) 474-482
32. Olsen J.A., and Smith R.D. Theory versus practice: a review of 'willingness-to-pay' in health and health care. Health Economics 10 1 (2001) 39-52
33. Payne J.W. Task complexity and contingent processing in decision making: an information search and protocol analysis. Organizational Behavior and Human Performance 16 (August 1976) 366-387
34. Payne J.W. Contingent decision behavior. Psychological Bulletin 92 2 (1982) 382-402
35. Payne J.W., Bettman J.R., and Johnson E.J. The adaptive decision maker (1993), Cambridge University Press, Cambridge
36. Phillips K.A., Maddala T., and Johnson F.R. Measuring preferences for health care interventions using conjoint analysis: an application to HIV testing. Health Services Research 37 6 (2002) 1681-1705
37. Ratcliffe J., Buxton M., McGarry T., Sheldon R., and Chancellor J. Patients' preferences for characteristics associated with treatments for osteoarthritis. Rheumatology 43 3 (2004) 337-345
38. Revelt D., and Train K. Mixed logit with repeated choices of appliance efficiency levels. Review of Economics and Statistics 80 4 (1998) 647-657
39. Rose J.M., and Black I.R. Means matter; but variance matters too: decomposing response latency influences on variance heterogeneity in stated preference experiments. Marketing Letters 17 (2006) 295-310
40. Ryan M., Scott D.A., Reeves C., Bate A., van Teijlingen E.R., Russell E.M., et al. Eliciting public preferences for healthcare: a systematic review of techniques. Health Technology Assessment 5 5 (2001) 1-186
41. Saelensminde K. The impact of choice inconsistency in stated choice studies. Environmental and Resource Economics 23 (2002) 403-420
42. Simonson I., and Tversky A. Choice in context: tradeoff contrast and extremeness aversion. Journal of Marketing Research 29 (August 1992) 281-295
43. Swait, J., & Adamowicz, W. The effect of choice complexity on random utility models: an application to combined stated and revealed preference models or tough choices: contribution or confusion? Association of Environmental and Resource Economists Workshop on Combining stated preference data and revealed preference data to estimate the demand for and/or benefits from environmental amenities, 1996, Tahoe City, CA.
44. Swait J., and Adamowicz W. The influence of task complexity on consumer choice: a latent class model of decision strategy switching. The Journal of Consumer Research 28 1 (2001) 135-148
45. Swait J., and Louviere J. The role of the scale parameter in the estimation and comparison of multinomial logit models. Journal of Marketing Research 30 (1993) 305-314
46. Train K. Discrete choice methods with simulation (2003), Cambridge University Press, Cambridge, UK
47. Train K., and Sonnier G. Mixed logit with bounded distributions of partworths. In: Alberini A., and Scarpa R. (Eds). Applications of simulation methods in environmental and resource economics (2004), Kluwer Academic Publisher, The Netherlands
48. Tversky A., Sattath S., and Slovic P. Contingent weighting in judgment and choice. Psychological Review 95 (1988) 371-384
49. Viney R., Savage E., and Louviere J.J. Empirical investigation of experimental design properties of discrete choice experiments in health care. Health Economics 14 4 (2005) 349-362
50. Wordswort S., Ryan M., Skatun D., and Waugh N. Women's preferences for cervical cancer screening: a study using discrete choice experiment. International Journal of Technological Assessment and Health Care 22 3 (2006) 344-350
51. Zwerina K., Huber J., and Kuhfeld W. A general method for constructing efficient choice designs (1996), Fuqua School of Business, Duke University, Durham, NC