A comparison of two experimental design approaches in applying conjoint analysis in patient-centered outcomes research: A randomized trial

Patient

Volumn 5, Issue 4, 2012, Pages 279-294

  Kinter, Elizabeth T ^a,b   Prior, Thomas J ^a   Carswell, Christopher I ^c   Bridges, John F P ^a  

^a JOHNS HOPKINS BLOOMBERG SCHOOL OF PUBLIC HEALTH   (United States)

^b Campbell Alliance   (United States)

^c ADIS INTERNATIONAL LIMITED   (New Zealand)

Author keywords

Conjoint analysis; Patient preference; Schizophrenia.

Indexed keywords

ADULT; ANALYTICAL PARAMETERS; ARTICLE; D EFFICIENT EXPERIMENTAL DESIGN; EXPERIMENTAL DESIGN; FEMALE; GERMANY; HUMAN; INTERMETHOD COMPARISON; MAJOR CLINICAL STUDY; MALE; ORTHOGONAL EXPERIMENTAL DESIGN; OUTCOME ASSESSMENT; OUTPATIENT; PREDICTIVE VALUE; PRIORITY JOURNAL; SCHIZOPHRENIA; STATISTICAL ANALYSIS; TASK PERFORMANCE;

ACTIVITIES OF DAILY LIVING; ADULT; ANTIPSYCHOTIC AGENTS; BASAL GANGLIA DISEASES; COGNITION; DECISION SUPPORT TECHNIQUES; FEMALE; HUMANS; INTERPERSONAL RELATIONS; MALE; OUTCOME ASSESSMENT (HEALTH CARE); PATIENT PREFERENCE; RECURRENCE; REPRODUCIBILITY OF RESULTS; RESEARCH DESIGN; SCHIZOPHRENIA;

EID: 84869186174     PISSN: 11781653     EISSN: 11781661     Source Type: Journal    
DOI: 10.2165/11641100-000000000-00000     Document Type: Article

References (69)

1. Bridges J, Kinter ET, Kidane L, et al. Things are looking up since we started listening to patients: trends in the application of conjoint analysis in health 1982-2007. Patient 2008; 1 (4):273-82
2. Marshall D, Bridges J, Hauber AB, et al. Conjoint analysis applications in health: how are studies being designed and reported? An update on current practice in the published literature between 2005 and 2008. Patient 2010; 3 (4):249-56
3. Ryan M, Gerard K. Using discrete choice experiments to value health care programmes: current practice and future research reflections. Appl Health Econ Health Policy 2003; 2 (1):55-64
4. de Bekker-Grob EW, Ryan M, Gerard K. Discrete choice experiments in health economics: a review of the literature. Health Econ 2012; 21 (2):145-72
5. Gustafsson A. Conjoint analysis as an instrument of market research practice. In: Gustafsson A, Huber F, editors. Conjoint measurement: methods and applications. Berlin: Springer, 2003:3-30
6. Adamowicz J, Williams M. Combining reveals preference and stated preference methods for valuing environmental amenities. J Environ Econ Manage 1994; 6:271-92 (Pubitemid 2070720)
7. Walley K, Parsons S, Bland M. Quality assurance and the consumer: a conjoint study. Br Food J 2000; 101 (2):48-161
8. Bridges JFP, Hauber AB, Marshall D, et al. A checklist for conjoint analysis applications in health: report of the ISPOR Good Research Practices for Conjoint Analysis Task Force. Value Health 2011; 14 (4):403-13
9. Viney R, Savage E, Louviere J. Empirical investigation of experimental design properties of discrete choice experiments in health care. Health Econ 2005 Apr; 14 (4):349-62 (Pubitemid 40514749)
10. Johnson F, Mansfield C. Survey-design and analytical strategies for better healthcare stated-choice studies. Patient 2008; 1 (4):299-307
11. Huber J, Zwerina K. The importance of utility balance in efficient choice designs. J Marketing Res 1996; 33:307-17
12. Swait J, Adamowicz W. The influence of task complexity on consumer choice: a latent class model of decision strategy switching. J Consum Res 2001; 28:135-48
13. Louviere J, Islam T, Wasi N, et al. Designing discrete choice experiments: do optimal designs come at a price? J Consum Res 2008; 35:360-75
14. Johnson FR, Lancsar E, Marshall D, et al. Constructing experimental designs for discrete-choice experiments: report of the ISPOR Conjoint Analysis Experimental Design Task Force. Value Health. In press
15. Street D, Burgess L, Viney R, et al. Designing discrete choice experiments for health care. In: Ryan M, Gerard K, Amaya-Amaya M, editors. Using discrete choice experiments to value health and health care: the economics of non-market goods and resources. Dordrecht: Springer, 2008
16. Zwerina K, Huber J, Kuhfeld W. A general method for constructing efficient choice designs. Durham (NC): Fuqua School of Business, Duke University, 1996
17. Dey A. Orthogonal fractional factorial designs. New York: Halstead Press, 1985
18. Caussade S, Ortuzar J de D, Rizzi LI, et al. Assessing the influence of design dimensions on stated choice experiment estimates. Transport Res B-Meth 2005 Aug; 39 (7):621-40 (Pubitemid 40306746)
19. Hensher DA. How do respondents process stated choice experiments? Attribute consideration under varying information load. J Appl Econom 2006 Sep 1; 21 (6):861-78 (Pubitemid 44662104)
20. Rose J, Hensher D, Caussade S, et al. Identifying differences in preferences due to dimensionality in stated choice experiments: a cross cultural analysis [abstract]. European Transport Conference; 2007 Oct 17-19; Leiden [online]. Available from URL: http://trid.trb.org/view.aspx?id= 855616 [Accessed 2012 Jan 18]
21. Hensher DA. Revealing differences in willingness to pay due to the dimensionality of stated choice designs: an initial assessment. Environ Resour Econ 2006 May; 34 (1):7-44
22. Hensher DA, Jou R-C, Rose JM, et al. A comparative investigation of the effects of the design dimensions of choice experiments on car commuters' route choice behaviours and valuation of time in Taiwan and Australia. Int J Transport 2011; 38 (2):147-72
23. DeShazo JR, Fermo G. Designing choice sets for stated preference methods: the effects of complexity on choice consistency. J Environ Econ Manag 2002; 44:123-43 (Pubitemid 34973730)
24. Pinnel J, Englert S. The number of choice alternatives in discrete choice modeling. In: Sawtooth Software, Inc. Sawtooth software conference proceedings. Sequim (WA): Sawtooth Software, Inc., 1997:121-54
25. Chrzan K, Fellerman R. A comparison of full-and partial-profile best/worst conjoint analysis. In: Sawtooth Software, Inc. Sawtooth software conference proceedings. Sequim (WA): Sawtooth Software, Inc., 1997:59-68
26. Rolfe J, Bennett J. The impact of offering two versus three alternatives in choice modelling experiments. Ecol Econ 2009; 68 (4):1140-8
27. Kjær T, Bech M, Gyrd-Hansen D, et al. Ordering effect and price sensitivity in discrete choice experiments: need we worry? Health Econ 2006; 15 (11):1217-28 (Pubitemid 44696949)
28. van Til JA, Stiggelbout AM, Ijzerman MJ. The effect of information on preferences stated in a choice-based conjoint analysis. Patient Educ Couns 2009 Feb; 74 (2):264-71
29. Bridges J, Buttorff C, Groothuis-Oudshoorn K. Estimating patients' preferences for medical devices: does the number of profiles in choice experiments matter? [NBER working paper no. 17482]. Cambridge (MA): National Bureau of Economic Research, 2011
30. Coast J, Flynn TN, Salisbury C, et al. Maximising responses to discrete choice experiments: a randomised trial. Appl Health Econ Health Policy 2006; 5 (4):249-60 (Pubitemid 46998482)
31. Fraenkel L. Feasibility of using modified adaptive conjoint analysis importance questions. Patient 2010; 3 (4):209-15
32. Griffith JM, Lewis CL, Hawley S, et al. Randomized trial of presenting absolute v. relative risk reduction in the elicitation of patient values for heart disease prevention with conjoint analysis. Med Decis Making 2009 Apr; 29 (2):167-74
33. Louviere J, Fox M, Moore W. Cross-task validity comparisons of stated preference choice models. Marketing Letters 1993; 4 (3):205-13
34. Louviere J, Hensher D, Swait J. Stated choice methods: analysis and application. Cambridge: Cambridge University Press, 2000
35. Hensher D, Rose J, Greene W. Applied choice analysis: a primer. 1st ed. Cambridge: Cambridge University Press, 2005
36. Bliemer M, Rose J. The design of stated choice experiments: the state of practice. Sydney (NSW): Institute of Transport Studies, University of Sydney, 2004
37. Carlsson F, Martinsson P. Design techniques for stated preference methods in health economics. Health Econ 2003; 12:281-94 (Pubitemid 36442817)
38. Kuhfeld WF. Efficient experimental designs using computerized searches [Sawtooth Research Paper Series]. Sequim (WA): Sawtooth Software, Inc., 1997 [online]. Available from URL: http://www.divms.uiowa.edu/~gwoodwor/ AdvancedDesign/KuhfeldTobiasGarratt.pdf [Accessed 2012 May 25]
39. Kanninen B. Optimal design for multinomial choice experiments. J Marketing Res 2002; 39:214-27
40. Sandor Z, Wedel M. Designing conjoint choice experiments using managers' prior beliefs. J Marketing Res 2001; 38:430-44
41. Sandor Z, Wedel M. Profile construction in experimental choice designs for mixed logit models. Market Sci 2002; 21:455-75
42. Sandor Z, Wedel M. Heterogeneous conjoint choice designs. J Marketing Res 2005; 42:210-8 (Pubitemid 40653435)
43. Fischer EP, Shumway M, Owen RR. Priorities of consumers, providers, and family members in the treatment of schizophrenia. Psychiatr Serv 2002; 53 (6):724-9 (Pubitemid 34568603)
44. Shumway M. Preference weights for cost-outcome analyses of schizophrenia treatments: comparison of four stakeholder groups. Schizophr Bull 2003; 29 (2):257-66 (Pubitemid 37187689)
45. Shumway M, Saunders T, Shern D, et al. Preferences for schizophrenia treatment outcomes among public policy makers, consumers, families and providers. Psychiatr Serv 2003; 54 (8):1124-8 (Pubitemid 36951513)
46. Bridges J, Jones C. Patient based health technology assessment: a vision of what might one day be possible. Int J Technol Assess Health Care 2007; 23 (1):30-5
47. Klag M, MacKenzie E, Carswell C, et al. The role of The Patient in promoting patient-centered outcomes research. Patient 2008; 1 (1):1-3
48. Kinter E, Schmeding A, Rudolph I, et al. Identifying patient-relevant endpoints among individuals with schizophrenia: an application of patient centered health technology assessment. Int J Technol Assess Health Care 2009; 25 (1):35-41
49. Bridges J, Cohen JP, Grist PG, et al. International experience with comparative effectiveness research: case studies from England/Wales and Germany. Adv Health Econ Health Serv Res 2010; 22:29-50
50. Caro JJ. Methods of economic evaluation for the German statutory healthcare system [letter]. Pharmacoeconomics 2009; 27 (3):263-4
51. Bridges J, Slawik L, Schmeding A, et al. A test of concordance between patient and psychiatrist valuations of multiple treatment goals for schizophrenia. Health Expect. Epub 2011 Jun 14
52. Kuhfeld W. Orthogonal arrays [TS-723]. Cary (NC): SAS [online]. Available from URL: http://support.sas.com/techsup/technote/ts723.html [Accessed 2012 Sep 27]
53. Miller S, Duncan B, Brown J, et al. The Outcome Rating Scale: a preliminary study of reliability, validity and feasibility of a brief visual analog measure. J Brief Ther 2003; 2 (2):91-100
54. Orme BK. Getting started with conjoint analysis: strategies for product design and pricing research. 2nd rev. ed. Madison (WI): Research Publishers LLC, 2010
55. McFadden D. Conditional logit analysis of qualitative choice behavior. In: Zarembka P, editor. Frontiers in econometrics. New York: Academic Press, 1974:105-42
56. Bridges J, Mohamed A, Finnern H, et al. Patients' preferences for treatment outcomes for advanced non-small cell lung cancer: a conjoint analysis. Lung Cancer 2012; 77:224-31
57. White H. Maximum likelihood estimation of misspecified models. Econometrica 1982 Jan; 50 (1):1-25
58. Train KE. Discrete choice methods with simulation. New York: Cambridge University Press, 2003
59. Swait J, Louviere J. The role of the scale parameter in the estimation and use of multinomial logit models. J Marketing Res 1993; 30:305-14
60. Viney R, Savage E, Louviere J. Empirical investigation of experimental design properties of discrete choice experiments in health care. Health Econ 2005; 14:349-62 (Pubitemid 40514749)
61. Morrison DG. On the interpretation of discriminant analysis. J Marketing Res 1969; 6 (2):156-63
62. Prinzie A, Van den Poel D. Random forests for multiclass classification: Random MultiNomial Logit. Expert Syst Appl 2008; 34:1721-32 (Pubitemid 350298198)
63. Burgess L. Discrete choice experiments [computer program]. Sydney (NSW): Department of Mathematical Sciences, University of Technology Sydney, 2007 [online]. Available from URL: http://crsu.science.uts.edu.au/choice. [Accessed 2012 Sep 27]
64. Street DJ, Burgess L. The construction of optimal stated choice experiments: theory and methods. Hoboken (NJ): Wiley, 2007
65. Finn A, Louviere J. Determining the appropriate response to evidence of public concern: the case of food safety. J Public Policy Mark 1992; 11:12-25
66. Bridges J, Searle S, Selck F. Engaging families in the design of social marketing strategies for male circumcision services in Johannesburg, South Africa. Social Market Q 2010; 16 (3):60-76
67. Bridges J, Selck F, Gray G, et al. Condom avoidance and determinants of demand for male circumcision in Johannesburg, South Africa. Health Policy Plann 2011; 26 (4):298-306
68. Louviere JJ, Flynn TN. Using best-worst scaling choice experiments to measure public perceptions and preferences for healthcare reform in Australia. Patient 2010 Dec 1; 3 (4):275-83
69. Gallego G, Bridges JF, Flynn T, et al. Using best-worst scaling in horizon scanning for hepatocellular carcinoma technologies. Int J Technol Assess Health Care 2012 Jul; 28 (3):339-46