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Sample Size Requirements for Discrete-Choice Experiments in Healthcare: a Practical Guide
Esther W de Bekker-Grob1, Bas Donkers2, Marcel F Jonker3
1Department of Public Health, Erasmus MC, University Medical Centre Rotterdam, PO Box 2040, 3000 CA, Rotterdam, The Netherlands. e.debekker@erasmusmc.nl.
The Patient
|March 2, 2015
Summary
Calculating adequate sample size for discrete-choice experiments (DCEs) in health economics is crucial. This paper guides researchers on minimum sample size requirements for statistical power in healthcare DCE studies.
Area of Science:
- Health Economics
- Patient Preference Analysis
- Stated Choice Modeling
Background:
- Discrete-choice experiments (DCEs) are widely used in health economics for policy analysis.
- Determining appropriate sample size for DCEs is a critical yet often unaddressed aspect.
- Existing sample size theories do not fully cover statistical power for hypothesis tests on DCE coefficients.
Purpose of the Study:
- To review current practices in sample size calculation for healthcare DCE studies.
- To explain the concept of required sample size for parameter estimation in DCEs.
- To offer a practical, step-by-step methodology for calculating minimum sample sizes in healthcare DCEs.
Main Methods:
- Literature review of sample size practices in healthcare DCEs.
- Theoretical explanation of sample size determination for DCE parameter estimates.
- Development of a practical guide for minimum sample size calculation.
Main Results:
- Identified gaps in current sample size calculation methods for healthcare DCEs.
- Provided a framework for understanding sample size needs based on statistical power.
- Detailed a step-by-step guide for calculating minimum sample sizes.
Conclusions:
- Standardized methods for sample size calculation in healthcare DCEs are needed.
- This paper provides essential guidance for researchers to ensure adequate statistical power.
- Implementing these methods will enhance the reliability of findings from healthcare DCE studies.
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