Department of Psychology, Palo Alto University, Palo Alto, CA, USA.
Behav Res Methods. 2019 Dec;51(6):2629-2645. doi: 10.3758/s13428-018-1117-5.
The actor-partner interdependence (APIM) and common-fate (CFM) models for dyadic data are well understood and widely applied. The actor and partner coefficients estimated in the APIM reflect the associations between individual-level variance components, whereas the CFM coefficient describes the association between dyad-level variance components. Additionally, both models assume that the theoretically relevant and/or empirically dominant component of variability resides at the same level (individual or dyad) across the predictor and outcome variables. The present work recasts the APIM and CFM in terms of dyadic nonindependence, or the extent to which a given variable reflects dyad- versus individual-level processes, and describes a pair of hybrid actor-partner and common-fate models that connect variance components residing at different levels. A series of didactic examples illustrate how the traditional APIM and CFM can be combined with the hybrid models to describe mediational processes that span the individual and dyad levels.
对双元数据的演员-伙伴相互依存关系(APIM)和共同命运(CFM)模型有很好的理解和广泛的应用。APIM 中估计的演员和伙伴系数反映了个体水平方差分量之间的关联,而 CFM 系数描述了对关系水平方差分量之间的关联。此外,这两个模型都假设在预测变量和结果变量中,理论上相关和/或经验上占主导地位的变异性成分位于同一水平(个体或对)。本工作根据对双元非独立性的重新解释,或给定变量反映对关系水平过程的程度,重新构建了 APIM 和 CFM,并描述了一对连接位于不同水平的方差分量的混合演员-伙伴和共同命运模型。一系列教学示例说明了如何将传统的 APIM 和 CFM 与混合模型相结合,以描述跨越个体和对关系水平的中介过程。