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Published in: The Patient - Patient-Centered Outcomes Research 5/2015

Open Access 01-10-2015 | Practical Application

Sample Size Requirements for Discrete-Choice Experiments in Healthcare: a Practical Guide

Authors: Esther W. de Bekker-Grob, Bas Donkers, Marcel F. Jonker, Elly A. Stolk

Published in: The Patient - Patient-Centered Outcomes Research | Issue 5/2015

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Abstract

Discrete-choice experiments (DCEs) have become a commonly used instrument in health economics and patient-preference analysis, addressing a wide range of policy questions. An important question when setting up a DCE is the size of the sample needed to answer the research question of interest. Although theory exists as to the calculation of sample size requirements for stated choice data, it does not address the issue of minimum sample size requirements in terms of the statistical power of hypothesis tests on the estimated coefficients. The purpose of this paper is threefold: (1) to provide insight into whether and how researchers have dealt with sample size calculations for healthcare-related DCE studies; (2) to introduce and explain the required sample size for parameter estimates in DCEs; and (3) to provide a step-by-step guide for the calculation of the minimum sample size requirements for DCEs in health care.
Appendix
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Footnotes
1
All aspects of our sample size calculation are conditional on the design of the experiment and the implementation in a questionnaire. The survey design will have an impact on the precision of the parameters that should be accounted for through its effect on the anticipated parameter values. Also, the model specification has an impact on the precision of the parameters.
 
2
The value of α (Sect. 3.1.1) is used to determine the corresponding quantile of the Normal distribution (z 1−α ) that is needed in the sample size calculations. The value of z 1−α for a given α can be found in the basic statistics textbooks or easily calculated in Microsoft Excel® using the formula NORMSINV(1−α). The value of z 1−α for an α of 0.05 equals 1.64.
 
3
In the computation of the sample size, we need z 1−β , the quantile of the Normal distribution with Φ(z 1−β ) = 1−β. Here again, Φ denotes the cumulative distribution function of the Normal distribution. Accordingly, the value for z 1–β for a given 1–β can be found in the basic statistics textbooks or easily calculated in Microsoft Excel® using the formula NORMSINV(1−β); e.g., assuming a statistical power level of 80 %, the value z 1−β is 0.84 [i.e., NORMSINV(0.8)].
 
4
A one-tailed test is used if only deviations in one direction are considered possible; in contrast, a two-tailed test is used if deviations of the estimated parameter in either direction from zero are considered theoretically possible. Be aware that, for a two-tailed test, the alpha level should be divided by 2 (i.e., α/2).
 
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Metadata
Title
Sample Size Requirements for Discrete-Choice Experiments in Healthcare: a Practical Guide
Authors
Esther W. de Bekker-Grob
Bas Donkers
Marcel F. Jonker
Elly A. Stolk
Publication date
01-10-2015
Publisher
Springer International Publishing
Published in
The Patient - Patient-Centered Outcomes Research / Issue 5/2015
Print ISSN: 1178-1653
Electronic ISSN: 1178-1661
DOI
https://doi.org/10.1007/s40271-015-0118-z

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