Abstract

Planned missing data designs allow researchers to have highly-powered studies by testing only a fraction of the traditional sample size. In two-method measurement planned missingness designs, researchers assess only part of the sample on a high-quality expensive measure, while the entire sample is given a more inexpensive, but biased measure. The present study focuses on a longitudinal application of the two-method planned missingness design. We provide evidence of the effectiveness of this design for fitting developmental data. Methodologically, we extend the framework for modeling an average treatment effect. Finally, we provide code and step-by-step instructions for how to analyze longitudinal, treatment effect data within these frameworks.

摘要

计划的缺失数据设计允许研究人员通过仅测试传统样本量的一小部分来进行高效研究。在两种方法测量计划缺失设计中，研究人员仅使用高质量昂贵的测量评估样本的一部分，而对整个样本给予更便宜但有偏差的测量。本研究侧重于两种方法计划缺失设计的纵向应用。我们提供了这种设计在拟合发育数据方面的有效性的证据。在方法论上，我们扩展了对平均治疗效果建模的框架。最后，我们提供了有关如何在这些框架内分析纵向治疗效果数据的代码和分步说明。