Considerations for analyzing EMA data (Oleson et al., 2021)

Purpose: The analysis of Ecological Momentary Assessment (EMA) data can be difficult to conceptualize due to the complexity of how the data are collected. The goal of this tutorial is to provide an overview of statistical considerations for analyzing observational data arising from EMA studies.Method: EMA data are collected in a variety of ways, complicating the statistical analysis. We focus on fundamental statistical characteristics of the data and general purpose statistical approaches to analyzing EMA data. We implement those statistical approaches using a recent study involving EMA.Results: The linear or generalized linear mixed-model statistical approach can adequately capture the challenges resulting from EMA collected data if properly set up. Additionally, while sample size depends on both the number of participants and the number of survey responses per participant, having more participants is more important than the number of responses per participant.Conclusion: Using modern statistical methods when analyzing EMA data and adequately considering all of the statistical assumptions being used can lead to interesting and important findings when using EMA.Supplemental Material S1. Power for given effect sizes, number of participants, and number of surveys per individual for a two independent groups comparison.Supplemental Material S2. Power for given effect sizes, number of participants, and number of surveys per individual for a paired groups comparison.Oleson, J. J., Jones, M. A., Jorgensen, E. J., & Wu, Y.-H. (2021). Statistical considerations for analyzing Ecological Momentary Assessment data. Journal of Speech, Language, and Hearing Research. Advance online publication. https://doi.org/10.1044/2021_JSLHR-21-00081

目的：由于生态瞬时评估（EMA）数据收集过程的复杂性，对其分析的概念化可能存在困难。本教程旨在概述分析源于EMA研究的观察性数据的统计考量。方法：EMA数据的收集方式多样，从而增加了统计分析的复杂性。我们专注于数据的根本统计特性以及分析EMA数据的一般性统计方法。我们通过一项涉及EMA的近期研究来实施这些统计方法。结果：若设置得当，线性或广义线性混合模型统计方法能够充分捕捉由EMA收集数据所导致的挑战。此外，样本量既取决于参与者的数量，也取决于每位参与者所进行的调查数量，但拥有更多的参与者比每位参与者的回答数量更为重要。结论：在分析EMA数据时采用现代统计方法，并充分考虑到所使用的所有统计假设，可利用EMA得出有趣且重要的发现。补充材料S1：对于两组独立比较，给定效应量、参与者和个人调查数量的功效。补充材料S2：对于配对组比较，给定效应量、参与者和个人调查数量的功效。Oleson, J. J., Jones, M. A., Jorgensen, E. J., & Wu, Y.-H. (2021). 分析生态瞬时评估数据的统计考量。言语、语言和听力研究杂志。在线预发表。https://doi.org/10.1044/2021_JSLHR-21-00081