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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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Treatment preferences of adults and adolescents with alopecia areata: A discrete choice experiment
Tervonen, T., Whichello, C. L., Law, E. H., Mauer, J., Mitra, D., Trapali, M., Krucien, N., & Hauber, B. (2023) · The Journal of Dermatology · doi:10.1111/1346-8138.17056 · Cited by 11
The value of genomic testing in severe childhood speech disorders
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“Following best practice recommendations, focus groups were conducted with parents of children experiencing severe speech disorders to identify attributes that were deemed important for the genomic testing decision-making process [23].”
BackgroundNurses’ job preferences on the internet plus nursing service program: a discrete choice experiment
He, Y., Feng, G., Wang, C., Yang, D., Hu, L., Ming, W., & Chen, W. (2024) · BMC Nursing · doi:10.1186/s12912-023-01692-0 · Cited by 12
“Following DCE guidelines [21], a qualitative approach could ensure that the attributes and levels of the questionnaire simulated realistic scenarios.”
MethodFeldman, S. R., Guérin, A., Gauthier‐Loiselle, M., Claxton, A. J., Hazra, N. C., Meng, Y., Gallant, K., & Balu, S. (2024) · Journal of Dermatological Treatment · doi:10.1080/09546634.2024.2345739 · Cited by 12
“The DCE portion of the study was conducted in accordance with the recommendations of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Good Research Practices for Conjoint Analysis Task Force (20,21).”
Preferences for COVID-19 Vaccines: Systematic Literature Review of Discrete Choice Experiments
Huang, Y., Feng, S., Zhao, Y., Wang, H., & Jiang, H. (2024) · JMIR Public Health and Surveillance · doi:10.2196/56546 · Cited by 12
“DCEs provide valuable insights into decision-making processes and allow for objective evaluation of attribute-based benefits [22-24].”
BackgroundRudolph, L., Freitag, M., & Thurner, P. W. (2024) · Public Opinion Quarterly · doi:10.1093/poq/nfae038 · Cited by 13
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Consumers Demand for Social Farming Products: An Analysis with Discrete Choice Experiments
Tempesta, T., Vecchiato, D., Nassivera, F., Bugatti, M., & Torquati, B. (2019) · Sustainability · doi:10.3390/su11236742 · Cited by 12
“A key aspect of the DCE preparation is the ‘experimental design’ [45], namely, the process that allows the researcher to build the choice sets that will be presented to respondents.”
BackgroundMacEwan, J. P., Gupte-Singh, K., Zhao, L. M., & Reckamp, K. L. (2020) · MDM Policy & Practice · doi:10.1177/2381468320922208 · Cited by 12
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Feldman, S. R., Poulos, C. M., Gilloteau, I., Mange, B., Boehm, K., Boeri, M., Naatz, M., & Augustin, M. (2021) · Journal of Dermatological Treatment · doi:10.1080/09546634.2020.1839007 · Cited by 12
Dam, T. H. T., Tur-Cardona, J., Speelman, S., Amjath-Babu, T. S., Sam, A. S., & Zander, P. M. (2021) · Agricultural Systems · doi:10.1016/j.agsy.2021.103090 · Cited by 12
Johnson, F. R., González, J. M., Yang, J., Özdemir, S., & Kymes, S. M. (2021) · Milbank Quarterly · doi:10.1111/1468-0009.12523 · Cited by 12
Sumpton, D., Kelly, A., Craig, J. C., Hassett, G., Kane, B., Oliffe, M., Tong, A., & Howell, M. (2021) · Arthritis Care & Research · doi:10.1002/acr.24782 · Cited by 12
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van der Worp, H., Brandenbarg, D., Boek, P. A., Braams, J. H. W., Brink, L. J. F., Keupers, J., & Blanker, M. H. (2021) · BMJ Open · doi:10.1136/bmjopen-2021-049916 · Cited by 12
Sigurdson, S. S., Harrison, M. J., Pearce, A. M., Richardson, H., Zaza, K. O., & Brundage, M. (2022) · Practical Radiation Oncology · doi:10.1016/j.prro.2021.08.012 · Cited by 12
Study of exit choice behaviour in metro station using partial immersive virtual reality
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“The study and experimental designs followed good practice guidelines [26,27].”
MethodGonzález, J. M., Johnson, F. R., Reed, S. D., Muiruri, C., Hutyra, C. A., & Mather, R. C. “. (2022) · Medical Decision Making · doi:10.1177/0272989x221115058 · Cited by 12
“Others employ sophisticated adaptive algorithms that extract more information per question but still may require numerous questions to obtain reliable results.(20) For some conditions, there is already evidence about the distribution of patient preferences in the population or clinically relevant patient types that ca…”
BackgroundWang, J., Zhou, L., Ni, Z., Wu, W., Liu, G., Fu, W., Zhang, X., & Tian, J. (2022) · Frontiers in Sustainable Food Systems · doi:10.3389/fsufs.2022.1019372 · Cited by 12
A Discrete Choice Analysis Comparing COVID-19 Vaccination Decisions for Children and Adults
Prosser, L. A., Wagner, A. L., Wittenberg, E., Zikmund‐Fisher, B. J., Rose, A. M., & Pike, J. J. (2023) · JAMA Network Open · doi:10.1001/jamanetworkopen.2022.53582 · Cited by 12
Physician Preferences when Selecting Candidates for Lower-Quality Kidney Offers
González, J. M., Mehrotra, S., Yang, J., Schantz, K., Becker, Y. T., Formica, R. N., Ladner, D. P., Kaufman, D. B., & Friedewald, J. J. (2023) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.0000000000000302 · Cited by 12
Kilambi, V., Johnson, F. R., González, J. M., & Mohamed, A. F. (2014) · Value in Health · doi:10.1016/j.jval.2014.09.001 · Cited by 12
Self-citationLilavanichakul, A., & Boecker, A. (2013) · RePEc: Research Papers in Economics · doi:10.22004/ag.econ.159659 · Cited by 12
Vanniyasingam, T., Daly, C., Jin, X., Zhang, Y., Foster, G., Cunningham, C. E., & Thabane, L. (2018) · Contemporary Clinical Trials Communications · doi:10.1016/j.conctc.2018.01.002 · Cited by 12
“Other studies have focussed on the reporting of applications of DCEs [39], and the details of DCEs and alternative approaches [40].”
BackgroundPoulos, C. M., Kinter, E. T., van Beek, J., Christensen, K., & Posner, J. (2018) · International Journal of Technology Assessment in Health Care · doi:10.1017/s0266462318000491 · Cited by 12
Athavale, A. S., Gooch, K. L., Walker, D. R., Suh, M., Scaife, J. G., Haber, A., Hadker, N., & Dmochowski, R. R. (2018) · Patient Preference and Adherence · doi:10.2147/ppa.s178668 · Cited by 12
“Current guidelines on the design of DCE studies highlight that most DCEs include between three and seven attributes.(11) Although the present study included ten attributes, these were carefully reviewed against clinical criteria and determined to best represent the hypothetical treatment profiles necessary for the DCE.”
Kim, H., Dowdy, D. W., Martinson, N. A., Kerrigan, D. L., Tudor, C., Golub, J. E., Bridges, J. F. P., & Hanrahan, C. F. (2018) · AIDS and Behavior · doi:10.1007/s10461-018-2324-x · Cited by 12
“Orthogonal main effect design is a simple, statistically efficient and valid design commonly used for discrete choice experiments, and allows for the to estimation ofe coefficients for main effects, assuming that two or higher-level interactions among factors are negligible [29].”
Self-citationRussell, B. J., Vogrin, S., Philip, J. A. M., Anderson, N. H., Collins, A., Burchell, J., Le, B. H. C., Brand, C. A., Hudson, P., & Sundararajan, V. (2019) · Journal of Pain and Symptom Management · doi:10.1016/j.jpainsymman.2019.08.009 · Cited by 12
Tervonen, T., Pignatti, F., & Postmus, D. (2019) · Medical Decision Making · doi:10.1177/0272989x19873630 · Cited by 11
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Abramova, O. (2022) · Electronic Markets · doi:10.1007/s12525-021-00505-z · Cited by 12
Natsky, A. N., Vakulin, A., Chai‐Coetzer, C. L., McEvoy, R. D., Adams, R., & Kaambwa, B. (2022) · Applied Health Economics and Health Policy · doi:10.1007/s40258-022-00716-1 · Cited by 13
What public health interventions do people in Canada prefer to fund? A discrete choice experiment
Card, K. G., Adshade, M., Hogg, R. S., Jollimore, J., & Lachowsky, N. J. (2022) · BMC Public Health · doi:10.1186/s12889-022-13539-5 · Cited by 12
Steinert, J., Sternberg, H., Veltri, G., & Büthe, T. (2022) · eLife · doi:10.7554/elife.79819 · Cited by 12
Hemodialysis patients’ preferences for the management of secondary hyperparathyroidism
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“To prepare the survey for online administration, the experimental design was developed following good research practices [11].”
MethodWang, C., Gu, Y., Zhao, L., Zhang, Y., Zhou, R., Gu, M., & Wang, L. (2022) · BMJ Open · doi:10.1136/bmjopen-2021-053277 · Cited by 11
Birch, K., Snider, J. T., Chiu, K., Baumgardner, J., Wade, S. W., & Shah, G. L. (2022) · Future Oncology · doi:10.2217/fon-2022-0421 · Cited by 11
Browne, E. N., Manenzhe, K. N., Makoni, W., Nkomo, S., Mahaka, I. C., Ahmed, K., Shapley‐Quinn, M. K., Marton, T., Luecke, E. H., Johnson, L. M., et al. (2023) · BMC Women s Health · doi:10.1186/s12905-023-02181-x · Cited by 11
Patients' preferences for chronic lymphocytic leukemia treatment: The CHOICE study
Sportoletti, P., Laurenti, L., Chiarenza, A., Gaïdano, G., Albi, E., Mauro, F. R., Trentin, L., Vallisa, D., Pane, F., Cuneo, A., et al. (2023) · Hematological Oncology · doi:10.1002/hon.3216 · Cited by 11
“23,24 27 The treatment options for CLL have undergone rapid evolution in recent years, to include also novel oral chemoimmunotherapy ‐ free agents, some of which are administered continuously until progression, while others are administered as time ‐ limited therapy involving fixed duration…”
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Filho, E. R. T., Hidalgo, L. G. S., de Lima, L. M., Spers, E. E., Pimentel, T. C., Esmerino, E. A., & da Cruz, A. G. (2023) · Journal of Food Science · doi:10.1111/1750-3841.16859 · Cited by 11
Jayalath, M. M., Perera, H. N., Seuring, S. A., & Thibbotuwawa, A. (2024) · Corporate Social Responsibility and Environmental Management · doi:10.1002/csr.2757 · Cited by 11
Mugambi, M. L., Odhiambo, B. O., Dollah, A., Marwa, M. M., Nyakina, J. N., Kinuthia, J., Baeten, J. M., Weiner, B. J., John-Stewart, G. C., Barnabas, R. V., et al. (2024) · Journal of the International AIDS Society · doi:10.1002/jia2.26301 · Cited by 11
Jiang, F., Feng, Y., Zong, W., Xue, J., Chen, W., Qi-zhi, L., Zhang, J., & Xu, A. (2024) · BMC Complementary Medicine and Therapies · doi:10.1186/s12906-024-04659-z · Cited by 13
Gilbert, C., Keay, L. J., Palagyi, A., Do, V. Q., McCluskey, P., White, A. J. R., Carnt, N. A., Stapleton, F. J., & Laba, T. (2018) · Clinical and Experimental Optometry · doi:10.1111/cxo.12653 · Cited by 11
“Recruitment ceased when thematic saturation occurred.(13,15) Each interview was audio-recorded, transcribed verbatim and coded by CP using NVivo software (Version 10, QSR International).”
MethodAntipsychotic choice: understanding shared decision-making among doctors and patients
Yeo, V., Dowsey, M. M., Alguera-Lara, V., Ride, J., Lancsar, E., & Castle, D. J. (2019) · Journal of Mental Health · doi:10.1080/09638237.2019.1630719 · Cited by 11
Self-citationAttributes Affecting User Decision to Adopt a Virtual Private Network (VPN) App
Sombatruang, N., Omiya, T., Miyamoto, D., Sasse, M. A., Kadobayashi, Y., & Baddeley, M. C. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-61078-4_13 · Cited by 11
Falahee, M., Simons, G., DiSantostefano, R. L., Valor, L., Radawski, C., Englbrecht, M., Bywall, K. S., Tcherny‐Lessenot, S., Kihlbom, U., Hauber, B., et al. (2021) · BMJ Open · doi:10.1136/bmjopen-2020-045851 · Cited by 11
“45 46”
Brouwers, J., Cox, B., Wilder, A. V., Claessens, F., Bruyneel, L., Ridder, D. J. M. K. D., Eeckloo, K., & Vanhaecht, K. (2021) · Health Policy · doi:10.1016/j.healthpol.2021.10.008 · Cited by 11
Coulibaly, L. P., Poder, T. G., & Tousignant, M. (2021) · International Journal of Health Policy and Management · doi:10.34172/ijhpm.2021.150 · Cited by 11
“The authors reported several attributes grouped into 15 main categories: 1) Accessibility,(14,31,36,40,41) 2) Distance,(14) 3) Interaction,(40) 4) Financial arrangements,(36) 5) Location,(14) 6) Training sessions,(35,38-40) 7) Time,(36) 8) Feeling safer,(30,36,39), 9) Confidence,(14,36) 10) Technology experience,(14,3…”
Amin, S., Tolaney, S. M., Cambron‐Mellott, M. J., Beusterien, K. M., Maculaitis, M. C., Mulvihill, E., Shinde, R., & McLaurin, K. K. (2022) · Future Oncology · doi:10.2217/fon-2021-0761 · Cited by 11
Xie, S., Wu, J. H., & Chen, G. (2022) · Quality of Life Research · doi:10.1007/s11136-022-03159-2 · Cited by 11
Assessing Italians' Preferences for Mountain Beef Production Using a Best–Worst Scaling Approach
Linder, M. O., Sidali, K. L., Fischer, C., Gauly, M., & Busch, G. (2022) · Mountain Research and Development · doi:10.1659/mrd-journal-d-21-00021.1 · Cited by 11
“The minimum sample size followed the rule of thumb applied to conjoint analysis (Reed Johnson et al 2013).”
MethodMoor, S. E., Tusubira, A. K., Wood, D., Akiteng, A. R., Galusha, D. H., Tessier‐Sherman, B., Hsieh, E., Ngaruiya, C., Rabin, T. L., Hawley, N. L., et al. (2022) · BMJ Open · doi:10.1136/bmjopen-2021-059949 · Cited by 11
Shields, G., Adrian Wells, A., Wright, S. J., Vass, C., Doherty, P., Capobianco, L., & Davies, L. M. (2022) · BMJ Open · doi:10.1136/bmjopen-2022-062503 · Cited by 11
Subscribing to new technology: consumer preferences for short-term ownership of electric vehicles
Carrel, A. L., White, L. V., Gore, C., & Shah, H. (2022) · Transportation · doi:10.1007/s11116-022-10353-1 · Cited by 11
“We note that a less efficient design, such as one that would have allowed more overlap between attribute levels (Reed Johnson et al. 2013), would likely have reduced ability to identify results, particularly given that a large share of coefficients is not significant (Sect.”
Alexandre, A. F., Morga, A., Thomas, C., Krucien, N., Tervonen, T., Jiletcovici, A., & Marsh, K. (2022) · Advances in Therapy · doi:10.1007/s12325-022-02367-z · Cited by 11
Kremer, I., Beaudart, C., Simons, J. J. M., Plieger, H., Schroeder, M., & Hiligsmann, M. (2023) · AIDS Care · doi:10.1080/09540121.2023.2240067 · Cited by 12
“A Bayesian e ffi cient experiment design with Ngene software (version 1.1.1) (Reed Johnson et al., 2013) was used to determine a subset of all possible ART pro fi les based on the selected attributes to present to respondents in the DCE.”
MethodInfluentialRaghunandan, R., Howard, K., Ilomäki, J., Hilmer, S. N., Gnjidic, D., & Bell, J. S. (2023) · Age and Ageing · doi:10.1093/ageing/afad153 · Cited by 11
Berchi, C., Dégieux, P., Halhol, H., Danel, B., Bennani, M., & Philippe, C. (2015) · International Journal of Pharmacy Practice · doi:10.1111/ijpp.12220 · Cited by 12
“It has been recently demonstrated that sample sizes less than 300 observations impacted DCE estimate precision.([19]) Therefore, results should be interpreted with caution.”
BackgroundUngar, W. J., Hadioonzadeh, A., Najafzadeh, M., Tsao, N., Dell, S., & Lynd, L. D. (2015) · BMC Pulmonary Medicine · doi:10.1186/s12890-015-0141-9 · Cited by 11
Preferences for locally grown products: evidence from a natural field experiment
Menapace, L., & Raffaelli, R. (2016) · European Review of Agricultural Economics · doi:10.1093/erae/jbw017 · Cited by 11
Hemodialysis patients’ preferences for the management of anemia
Hauber, B., Caloyeras, J. P., Posner, J., Brommage, D., Tzivelekis, S., & Pollock, A. S. (2017) · BMC Nephrology · doi:10.1186/s12882-017-0664-9 · Cited by 12
“To prepare the survey for online administration, experimental designs for both the DCE and BWS exercises were developed following good research practices [14].”
MethodPricing Inputs and Outputs: Market Prices Versus Shadow Prices, Market Power, and Welfare Analysis
Bhattacharyya, A., Kutlu, L., & Sickles, R. C. (2019) · Springer eBooks · doi:10.1007/978-3-030-23727-1_13 · Cited by 11
Ju, A., Unruh, M. L., Davison, S. N., Dapueto, J. J., Dew, M. A., Fluck, R., Germain, M. J., Jassal, S. V., Obrador, G. T., O'Donoghue, D. J., et al. (2019) · Nephrology · doi:10.1111/nep.13638 · Cited by 11
Hardtstock, F., Sbarigia, U., Kocaata, Z., Wilke, T., & Sylvester, S. V. (2020) · Patient Preference and Adherence · doi:10.2147/ppa.s238833 · Cited by 11
Preferences of Canadian Patients and Physicians for Treatment of HR+/HER2− Advanced Breast Cancer
Stellato, D., Thabane, M. E., Eichten, C., & Delea, T. E. (2021) · Current Oncology · doi:10.3390/curroncol28010051 · Cited by 12
“The DCE was developed in a manner consistent with the published recommendations [19,21,22].”
MethodResultCalculating Utilities From the Spine Oncology Study Group Outcomes Questionnaire
Pahuta, M., Fisk, F. E., Versteeg, A., Fisher, C., Sahgal, A., Gokaslan, Z., Reynolds, J., Laufer, I., Lazary, Á., Rhines, L., et al. (2021) · Spine · doi:10.1097/brs.0000000000003981 · Cited by 7
Neurotization Preferences in Smile Reanimation: A Discrete Choice Experiment
Dusseldorp, J. R., Naunheim, M. R., Quatela, O. E., Fortier, E., Hadlock, T. A., & Jowett, N. (2021) · Plastic & Reconstructive Surgery · doi:10.1097/prs.0000000000008302 · Cited by 11
Mighton, C. E., Clausen, M., Sebastian, A., Muir, S. M., Shickh, S., Baxter, N. N., Scheer, A. S., Glogowski, E., Schrader, K. A., Thorpe, K. E., et al. (2021) · Human Genetics · doi:10.1007/s00439-021-02366-0 · Cited by 12
Self-citationFotheringham, J., Vilar, E., Bansal, T., Laboi, P., Davenport, A., Dunn, L., & Hole, A. R. (2021) · American Journal of Kidney Diseases · doi:10.1053/j.ajkd.2021.09.012 · Cited by 11
Wang, K., Wong, E. L., Wong, A., Cheung, A. W.-L., & Yeoh, E. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19020686 · Cited by 11
“, zero prior mean, all levels of each attribute were set to be equally preferable in the design) D-optimal design was used to select 36 choice sets with 2 alternatives in each of the choice sets from a full factorial design that consists of 23,220 different choice sets [18].”
MethodPatient preferences for mitral valve regurgitation treatment: a discrete choice experiment
Janssen, E. M., Keuffel, E. L., Liden, B., Hanna, A., & Rizzo, J. A. (2022) · Postgraduate Medicine · doi:10.1080/00325481.2021.2020571 · Cited by 11
Preferences of Older People With a Life-Limiting Illness: A Discrete Choice Experiment
Johnston, B. M., Daveson, B. A., Normand, C. E. M., Ryan, K., Smith, M., McQuillan, R., Higginson, I. J., Selman, L. E., & Tobin, K. (2022) · Journal of Pain and Symptom Management · doi:10.1016/j.jpainsymman.2022.04.180 · Cited by 11
Valuing Individuals’ Preferences and Health Choices of Physical Exercise
Aboagye, E. (2017) · Pain and Therapy · doi:10.1007/s40122-017-0067-4 · Cited by 12
Art and Science of Instrument Development for Stated-Preference Methods
Janssen, E. M., & Bridges, J. F. P. (2017) · Patient · doi:10.1007/s40271-017-0261-9 · Cited by 11
Self-citationKamara, J. S. (2018) · International Journal of Health Economics and Policy · doi:10.11648/j.hep.20180301.11 · Cited by 11
“This raises few issues mainly to determine the overall policy objective and the type of choice experiment to be designed [18, 23, 34], which we consider in the next subsections.”
Eliciting women’s preference for prenatal testing in China: a discrete choice experiment
Wu, L., Wu, Y., Zou, S., Sun, C., Chen, J., Li, X., Lin, Z., Guan, L., Zeng, Q., Zhao, S., et al. (2020) · BMC Pregnancy and Childbirth · doi:10.1186/s12884-020-03270-7 · Cited by 11
Preferences for Energy Retrofit Investments Among Low-income RentersPreprint
Schmitz, H., & Madlener, R. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4119596 · Cited by 11
Valuing mangrove ecosystem services along the Brazilian Amazon coast
Otieno, P., Owuor, M. A., Pacheco, C. F. O., Coppo, G., Santos, T. M., Ferreira, T. O., & Bernardino, A. F. (2026) · Ecosystem Services · doi:10.1016/j.ecoser.2026.101831 · Cited by 11
Jin, S., Tan, Z., Liu, T., Chan, S. N., Sheng, J., Wong, T.-H., Huang, J. V., Zhang, C. J. P., & Ming, W. (2022) · JMIR Serious Games · doi:10.2196/34586 · Cited by 14
Public Valuation of Direct Restorations: A Discrete Choice Experiment
Bailey, O., Stone, S. J., Ternent, L., & Vernazza, C. R. (2022) · Journal of Dental Research · doi:10.1177/00220345221108699 · Cited by 10
“Sample size calculations for DCEs are imprecise (Bridges et al. 2011; Johnson et al. 2013).”
BackgroundResultMa, H., Jia, E., Ma, H., Pan, Y., Jiang, S., & Xiong, J. (2023) · Frontiers in Public Health · doi:10.3389/fpubh.2023.1050407 · Cited by 10
Xie, Z., Liu, H., & Or, C. K. (2023) · mHealth · doi:10.21037/mhealth-22-39 · Cited by 11
Govathson, C., Long, L. C., Moolla, A., Mngadi-Ncube, S., Ngcobo, N., Mongwenyana, C., Lince-Deroche, N., & Pascoe, S. J. S. (2023) · BMC Health Services Research · doi:10.1186/s12913-023-10414-w · Cited by 11
Do consumers want reconditioned electric vehicle batteries? – A discrete choice experiment
Huster, S., Rosenberg, S., Hufnagel, S., Rudi, A., & Schultmann, F. (2024) · Sustainable Production and Consumption · doi:10.1016/j.spc.2024.05.027 · Cited by 11
“While this sample size is reasonable, as Johnson et al. (2013) found that the precision of studies typically does not increase significantly beyond 300 observations, it is important to note that the analysis entailed sub-groups of much lower size (cf. Table 2).”
Fifer, S. J., Godsell, J., Opat, S., Hamad, N., Lasica, M., Forsyth, C. J., Morand, L., Smeaton, E., Winton, S., Puig, A., et al. (2024) · BMC Cancer · doi:10.1186/s12885-024-12589-9 · Cited by 11
Saldarriaga, E. M., Chen, Y., Montaño, M. A., Thuo, N. B., Kiptinness, C., Terris‐Prestholt, F., Stergachis, A. S., Mugambi, M. L., Ngure, K., Ortblad, K. F., et al. (2024) · Journal of the International AIDS Society · doi:10.1002/jia2.26356 · Cited by 8
Hilo, A. A., & McPeak, J. G. (2024) · BMC Health Services Research · doi:10.1186/s12913-024-11971-4 · Cited by 15
“This design employed a full-profile, conjoint-based choice approach with balanced overlap to minimize the number of choices presented to respondents [45, 46].”
Buzan, J., & Sheehy‐Skeffington, J. (2024) · Journal of Social Issues · doi:10.1111/josi.12658 · Cited by 8
Patient preferences for Remote cochlear implant management: A discrete choice experiment
Sucher, C. M., Norman, R., Chaffey, E. L., Bennett, R. J., & Ferguson, M. (2025) · PLoS ONE · doi:10.1371/journal.pone.0320421 · Cited by 10
McGrady, M. E., Prosser, L. A., Thompson, A. N., & Pai, A. L. H. (2017) · Journal of Pediatric Psychology · doi:10.1093/jpepsy/jsx104 · Cited by 10
“…(each attribute level occurs the same number of times), Downloaded from https://academic.oup.com/jpepsy/article-abstract/43/2/172/4034678 by guest on 27 July 2018 and demonstrate minimal overlap (two alternatives should not exhibit the same level for a given attribute; Johnson et al., 2013).”
BackgroundMethodXu, T., Ni, Q., Yao, L., Qiao, D., & Zhao, M. (2020) · Discrete Dynamics in Nature and Society · doi:10.1155/2020/1345054 · Cited by 10
“If all the possible CE questionnaires were tested, it would take a massive amount of labor and resources and would be difficult to achieve [44, 45].”
BackgroundDorgali, M. V., Longo, A., Vass, C., Shields, G., Harrison, R. S., Riccardo Scarpa, A., & Boeri, M. (2021) · PharmacoEconomics · doi:10.1007/s40273-021-01076-9 · Cited by 10
Saldarriaga, E. M., Hauber, B., Carlson, J. J., Barthold, D., Veenstra, D. L., & Devine, B. (2021) · Value in Health · doi:10.1016/j.jval.2021.09.016 · Cited by 10
Rieger, E., Prasetya, K., Christensen, B. K., & Shou, Y. (2021) · International Journal of Eating Disorders · doi:10.1002/eat.23634 · Cited by 10
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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