Department of Psychology, Universität Tübingen, Tübingen, Germany.
Psychol Methods. 2012 Dec;17(4):623-41. doi: 10.1037/a0029314. Epub 2012 Aug 27.
This article derives the power curves for a Wald test that can be applied to randomized response models when small prevalence rates must be assessed (e.g., detecting doping behavior among elite athletes). These curves enable the assessment of the statistical power that is associated with each model (e.g., Warner's model, crosswise model, unrelated question model, forced-choice models, item count model, cheater detection model). This power analysis can help in choosing the optimal model and sample size and in setting model parameters in survey studies. The general framework can be applied to all existing randomized response model versions. The Appendix of this article contains worked-out numerical examples to demonstrate the power analysis for each specific model.
本文推导出了 Wald 检验的功效曲线,可应用于必须评估小流行率的随机响应模型(例如,检测精英运动员中的兴奋剂行为)。这些曲线可评估与每个模型相关联的统计功效(例如,Warner 模型、交叉模型、无关问题模型、强制选择模型、项目计数模型、作弊者检测模型)。这种功效分析有助于选择最佳模型和样本量,并在调查研究中设置模型参数。一般框架可应用于所有现有的随机响应模型版本。本文的附录包含了具体模型的功效分析的实例。