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Constructing Experimental Designs for Discrete-Choice Experiments: Report of the ISPOR Conjoint Analysis Experimental Design Good Research Practices Task Force
Open accessAbstract
Stated-preference methods are a class of evaluation techniques for studying the preferences of patients and other stakeholders. While these methods span a variety of techniques, conjoint-analysis methods-and particularly discrete-choice experiments (DCEs)-have become the most frequently applied approach in health care in recent years. Experimental design is an important stage in the development of such methods, but establishing a consensus on standards is hampered by lack of understanding of available techniques and software. This report builds on the previous ISPOR Conjoint Analysis Task Force Report: Conjoint Analysis Applications in Health-A Checklist: A Report of the ISPOR Good Research Practices for Conjoint Analysis Task Force. This report aims to assist researchers specifically in evaluating alternative approaches to experimental design, a difficult and important element of successful DCEs. While this report does not endorse any specific approach, it does provide a guide for choosing an approach that is appropriate for a particular study. In particular, it provides an overview of the role of experimental designs for the successful implementation of the DCE approach in health care studies, and it provides researchers with an introduction to constructing experimental designs on the basis of study objectives and the statistical model researchers have selected for the study. The report outlines the theoretical requirements for designs that identify choice-model preference parameters and summarizes and compares a number of available approaches for constructing experimental designs. The task-force leadership group met via bimonthly teleconferences and in person at ISPOR meetings in the United States and Europe. An international group of experimental-design experts was consulted during this process to discuss existing approaches for experimental design and to review the task force's draft reports. In addition, ISPOR members contributed to developing a consensus report by submitting written comments during the review process and oral comments during two forum presentations at the ISPOR 16th and 17th Annual International Meetings held in Baltimore (2011) and Washington, DC (2012).
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“We followed recommended guidelines to design and implement the DCE. [7, 8, 11–16]”
From Assessing the American public's preferences for reforms to teen driving licensure systems: a discrete choice experiment (2026) · cites this paper as [12]
In the citing paper
“To improve experimental efficiency and avoid redundancy, this study adopted a D-efficient design, which reduces the number of choice cards while maintaining the precision of parameter estimation, thereby enabling participants to provide more efficient data contributions within a limited number of tasks (59, 60).”
From Designing age-friendly interfaces and wearable–environment integrations to enhance medication adherence: a discrete choice experiment among older adults (2026) · cites this paper as [59]
In the citing paper
“we used an efficient fractional factorial design to generate 7 choice scenarios, maximizing D-efficiency with zero priors on the coefficients. [12, 15]”
From Assessing the American public's preferences for reforms to teen driving licensure systems: a discrete choice experiment (2026) · cites this paper as [12]
In the citing paper
“The most widely used type of stated preference method is the discrete choice experiment (DCE) [7].”
From Understanding Uptake of Digital Health Products: Methodology Tutorial for a Discrete Choice Experiment Using the Bayesian Efficient Design (2021) · cites this paper as [7]
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“DCEs have been used to study the treatment preferences of patients with depression (Dwight-Johnson et al., 2004) and schizophrenia (Levitan et al., 2015), parents of children with attention-deficit/hyperactivity disorder (Waschbusch et al., 2011), patient-centred care preferences (Cunningham et al., 2008b) and prefere…”
MethodInfluentialSymposium Title: Preference Evidence for Regulatory Decisions
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“Committees of researchers in organizations such as ISPOR (International Society for Pharmacoeconomics and Outcomes Research) and IAHPR (International Academy of Health Preference Research) are actively developing consensus guidance on stated-preference study design, experimental design, and analysis [5, 15, 16].”
A novel measure of drug benefit–risk assessment based on Scale Loss Score
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“preferences have been widely studied in the literature,(11,12,39,40,42,43,45) among which Discrete Choice Experiment and Swing-Weighting appeared to be appropriate in terms of theoretical foundations, cognitive burden, feasibility and robustness.(16,44,47,48) In the MCDA framework, the weight assigned to one criterion…”
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“Generally, the higher number of attributes in a traditional choice study requires a larger sample.(30) For example, Laba and colleagues required a sample of 503 participants for a study that included 7 attributes and 20 levels,(11) while Ratcliffe and colleagues recruited 412 participants to study 5 attributes and 15…”
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“Assessment of stochastic dominance using the Mean-Gini relaxes these assumptions, just requiring that decision makers are risk averse [42,59].”
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“This customized list consists mostly of positive emotions, which is in agreement with the results obtained in other studies on product emotions, considering that food experiences are mainly positive [53,54].”
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“A discrete choice experiment is usually administered through a questionnaire than contains [at least] three parts: a) an introduction, 2) the DCE itself, 3) respondent information [1].”
BackgroundMethodA Bayesian hierarchical model for discrete choice data in health care
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“24 The identity of the human participants in this study cannot be directly ascertained, and the investigator did not contact or re-identify participants; therefore, the study received exemption from the Western Institutional Review Board.”
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Afful-Dadzie, E., & Afful‐Dadzie, A. (2021) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2021.100064 · Cited by 9
Patient Preferences for Outcomes Following DCIS Management Strategies: A Discrete Choice Experiment
Chapman, B. M., Yang, J., González, J. M., Havrilesky, L. J., Reed, S. D., & Hwang, E. S. (2021) · JCO Oncology Practice · doi:10.1200/op.20.00614 · Cited by 9
“These constructed health profiles are designed to evaluate when adverse health outcomes resulting from various management strategies would have outweighed the benefit of reducing the risk of invasive breast cancer rather than direct comparisons of risks and benefits between real-life options.(16)”
BackgroundBastien, G., Grande, C. D., Dyachenko, A., Kaczorowski, J. A., Pagé, M. G., Brissette, S., Lespérance, F., Dubreucq, S., Hooley, P., & Jutras‐Aswad, D. (2021) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2021.108857 · Cited by 9
Karunaratna, S., Weerasinghe, M. C., Ranasinghe, T., Jayasuriya, R., Chandraratne, N., Herath, H., & Quaife, M. (2021) · Health Policy and Planning · doi:10.1093/heapol/czab141 · Cited by 9
“The 11 th task was a dominant task created by the researchers to assess rationality in responses (Johnson et al. 2013; Trevonen et al. 2018) The 12 th task was a repeat of the 3 rd task to assess reliability of responses (Mangham et al.”
MethodImbert, E., Hickey, M. D., Rosario, J. B. D., Conte, M., Kerkhoff, A. D., Clemenzi-Allen, A., Riley, E. D., Havlir, D. V., & Gandhi, M. (2022) · JAIDS Journal of Acquired Immune Deficiency Syndromes · doi:10.1097/qai.0000000000002929 · Cited by 11
Simblett, S. K., Pennington, M., Quaife, M., Theochari, E., Burke, P., Brichetto, G., Devonshire, J., Lees, S., Little, A. A., Pullen, A., et al. (2022) · JMIR Formative Research · doi:10.2196/29509 · Cited by 9
What Outcomes Are Most Important to Patients Following a Lower Extremity Limb-threatening Injury?
Wong, A. L., Burke, C. E., Bangura, A., O’Hara, N. N., Mundy, L. R., O’Toole, R. V., & Pensy, R. A. (2022) · Annals of Surgery · doi:10.1097/sla.0000000000005470 · Cited by 9
Stated Choice design comparison in a developing country: recall and attribute nonattendance
Iles, R. A., & Rose, J. M. (2014) · Health Economics Review · doi:10.1186/s13561-014-0025-3 · Cited by 9
Talati, Z., Pettigrew, S., Dixon, H., Neal, B. C., Hughes, C., Shilton, T., & Miller, C. L. (2017) · BMC Nutrition · doi:10.1186/s40795-016-0119-x · Cited by 9
von Arx, L., Johnson, F. R., Mørkbak, M. R., & Kjær, T. (2017) · Value in Health · doi:10.1016/j.jval.2016.11.023 · Cited by 9
Patient and Public Preferences for Treatment Attributes in Parkinson’s Disease
Weernink, M. G. M., van Til, J. A., Groothuis‐Oudshoorn, C. G. M., & IJzerman, M. J. (2017) · Patient · doi:10.1007/s40271-017-0247-7 · Cited by 9
Nichols, E., O’Hara, N. N., Degani, Y., Sprague, S., Adachi, J. D., Bhandari, M., Holick, M. F., Connelly, D. W., & Slobogean, G. P. (2018) · BMJ Open · doi:10.1136/bmjopen-2017-019685 · Cited by 9
“patterns of 397 orthopaedic surgeons.(13) 134”
Barker, A. L., Peeters, G. M. E. E., Morello, R., Norman, R., Ayton, D., Lefkovits, J., Brennan, A., Evans, S., Zalcberg, J. R., Reid, C. M., et al. (2018) · BMJ Open · doi:10.1136/bmjopen-2018-023141 · Cited by 9
Patient and caregiver preferences for haemophilia A treatments: A discrete choice experiment
Su, J., Li, N., Joshi, N., Ng, X., Botteman, M. F., Shah, R., Jain, N., Lyn, N., & Preblick, R. (2020) · Haemophilia · doi:10.1111/hae.14137 · Cited by 9
Exploring Older Swiss People’s Preferred Dental Services for When They Become Dependent
Chebib, N., Abou‐Ayash, S., Maniewicz, S., Srinivasan, M., Hill, H. R., McKenna, G. J., Holmes, E. A. F., Schimmel, M., Brocklehurst, P. R., & Müller, F. (2020) · SWISS DENTAL JOURNAL SSO – Science and Clinical Topics · doi:10.61872/sdj-2020-11-690 · Cited by 9
Welk, B. K., Myers, J. B., Kennelly, M., Elliott, C. S., McKibbon, M., Watson, J., & Gervais, K. (2021) · Neurourology and Urodynamics · doi:10.1002/nau.24730 · Cited by 9
“In keeping with standard methodology, we identified the key attributes, assigned levels to the attributes, created the final survey, and then pretested the survey.(10) As part of this project, we started with a qualitative study to identify and explore key psychosocial themes related to bladder management in a represe…”
MethodPublic preferences for safe consumption sites for opioid use: A discrete choice experiment
Berrigan, P., & Zucchelli, E. (2022) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2022.109578 · Cited by 8
Conte, M., Zimba, R., Fong, C., Carmona, J. M., Gambone, G. F., Robertson, M. M., Kozlowski, S., Abdelqader, F., Nash, D., & Irvine, M. K. (2023) · Journal of the International AIDS Society · doi:10.1002/jia2.26162 · Cited by 8
“We presented clients with 10 choice tasks to minimize cognitive burden and maintain design efficiency [18].”
MethodToiba, H., Noor, A. Y. M., Rahman, M., & Riana, F. (2023) · Journal of Environmental Planning and Management · doi:10.1080/09640568.2023.2269308 · Cited by 8
Watson, D. L., Listerud, L., Drab, R., Lin, W., Momplaisir, F. M., & Bauermeister, J. A. (2024) · Journal of the International AIDS Society · doi:10.1002/jia2.26211 · Cited by 8
Gawronski, B. E., Salloum, R. G., & Duarte, J. D. (2024) · Frontiers in Pharmacology · doi:10.3389/fphar.2024.1384667 · Cited by 9
Schein, J. R., Cloutier, M., Gauthier‐Loiselle, M., Catillon, M., Meng, Y., Libchaber, B., Jiang, F., & Childress, A. C. (2024) · Patient Preference and Adherence · doi:10.2147/ppa.s467724 · Cited by 9
Ornstein, M. C., Rosenblatt, L. C., Yin, X., Tejo, V. D., Guttenplan, S. B., Ejzykowicz, F., Beusterien, K. M., Will, O., Mackie, D. S., Skiles, G., et al. (2024) · Patient Preference and Adherence · doi:10.2147/ppa.s460994 · Cited by 8
“This study was conducted according to the International Society for Pharmacoeconomics and Outcomes guidelines on conjoint analysis 22–24”
BackgroundMethodWang, K., Yang, Q., Wan, L., & An, J. (2024) · Frontiers in Public Health · doi:10.3389/fpubh.2024.1479237 · Cited by 8
Zhang, L., Li, X., Chen, J., Wang, X., & Sun, Y. (2024) · JMIR Public Health and Surveillance · doi:10.2196/57798 · Cited by 8
Aschmann, H. E., Musinguzi, A., Kadota, J. L., Namale, C., Kakeeto, J., Nakimuli, J., Akello, L., Welishe, F., Nakitende, A., Berger, C. A., et al. (2024) · Journal of the International AIDS Society · doi:10.1002/jia2.26390 · Cited by 5
Buse, S., & Meyerding, S. G. H. (2025) · Journal of Agriculture and Food Research · doi:10.1016/j.jafr.2025.101690 · Cited by 9
Schoot, T. S., van Til, J. A., Groothuis‐Oudshoorn, C. G. M., Rombeek, C., Lusseveld, M. J., van Marum, R. J., Hilbrands, L. B., & Kerckhoffs, A. P. M. (2025) · American Journal of Kidney Diseases · doi:10.1053/j.ajkd.2025.06.010 · Cited by 8
Sadreghaemy, M., Philbert, D., Heerdink, E. R., Bouvy, M. L., Egberts, T. C. G., & Bloem, L. T. (2025) · British Journal of Clinical Pharmacology · doi:10.1002/bcp.70244 · Cited by 8
“22,23 Given the large size of the AMP patient panel and a prior study indicating high response rates by the panel, 28 the number of respondents for this study was expected to be higher than 300.”
O’Connor, A., Krucien, N., Cantillon, P., Parker, M., & McCurtin, A. (2020) · Physiotherapy · doi:10.1016/j.physio.2020.04.003 · Cited by 8
Yang, J., Reed, S. D., Hass, S., Skeen, M. B., & Johnson, F. R. (2021) · Medical Decision Making · doi:10.1177/0272989x20979833 · Cited by 8
Tencer, T., Will, O., Kumar, J., Cambron‐Mellott, M. J., Mackie, D. S., & Beusterien, K. M. (2021) · Current Medical Research and Opinion · doi:10.1080/03007995.2021.1940911 · Cited by 8
Metadata
- Authors
- Reed Johnson, F., Lancsar, E., Marshall, D., Kilambi, V., Mühlbacher, A., Regier, D. A., Bresnahan, B. W., Kanninen, B., & Bridges, J. F. P.
- Affiliations
- Monash University (AU)
- University of Calgary (CA)
- RTI Health Solutions (US)
- Duke University (US)
- BC Cancer Agency (CA)
- University of Washington (US)
- Johns Hopkins University (US)
- ORCID
- Venue
- Value in Health
- Publisher
- Elsevier BV
- Published
- 2013-01
- Volume
- 16
- Issue
- 1
- Pages
- 3-13
- ISSN
- 1098-3015 (ISSN-L)
- OpenAlex
- W2159936838
- Cited by
- 1,799
- References
- 51
- Citations by year
- 2026: 158 · 2025: 181 · 2024: 213 · 2023: 162 · 2022: 190 · 2021: 186 · 2020: 150 · 2019: 117 · 2018: 109 · 2017: 109 · 2016: 99 · 2015: 56 · 2014: 50 · 2013: 15
- FWCI
- 171.60
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Value in Health (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Economic and Environmental Valuation
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
- Social Sciences › Decision Sciences › Management Science and Operations Research › Optimal Experimental Design Methods
- Keywords
- discrete choice experiment, experimental design, stated preference methods, conjoint analysis, health care preferences, choice models, good scientific practice
- MeSH terms
- Choice Behavior, Delivery of Health Care, Humans, International Cooperation, Research Design, Models, Statistical, Patient Preference
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