二元体
范畴变量
心理学
适度
纵向研究
协变量
自回归模型
多级模型
功率(物理)
合作伙伴效应
计量经济学
纵向数据
二次方程
社会心理学
计算机科学
统计
数学
机器学习
数据挖掘
量子力学
物理
几何学
作者
Ginette Lafit,Laura Sels,Janne Adolf,Tom Loeys,Eva Ceulemans
标识
DOI:10.1177/02654075221080128
摘要
The longitudinal actor–partner interdependence model (L-APIM) is used to study actor and partner effects, both linear and curvilinear, in dyadic intensive longitudinal data. A burning question is how to conduct power analyses for different L-APIM variants. In this paper, we introduce an accessible power analysis application, called PowerLAPIM, and provide a hands-on tutorial for conducting simulation-based power analyses for 32 L-APIM variants. With PowerLAPIM, we target the number of dyads needed, but not the number of repeated measurements for both partners (which is often fixed in longitudinal studies). PowerLAPIM allows to study moderation of linear and quadratic actor and partner effects by incorporating time-varying covariates or a categorical dyad-level predictor to test group differences. We also provide the functionality to account for serial dependency in the outcome variable by including autoregressive effects. Building on existing study that can yield estimates and thus plausible values of relevant model parameters, we illustrate how to perform a power analysis for a future study. In this illustration, we also demonstrate how to run a sensitivity analysis, to assess the impact of uncertainty about the model parameters, and of changes in the number of repeated measurements.
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