二元体
结构方程建模
独立性(概率论)
心理学
多级模型
纵向数据
感觉
合作伙伴效应
社会心理学
计算机科学
数学
统计
数据挖掘
机器学习
作者
Fien Gistelinck,Tom Loeys
标识
DOI:10.1080/10705511.2018.1527223
摘要
In dyadic research, the actor–partner interdependence model (APIM) is widely used to model the effect of a predictor measured across dyad members on one’s own and one’s partner outcome. When such dyadic data are measured repeatedly over time, both the non-independence within couples and the non-independence over time need to be accounted for. In this paper, we present a longitudinal extension of the APIM, the L-APIM, that allows for both stable and time-varying sources of non-independence. Its implementation is readily available in multilevel software, such as proc mixed in SAS, but is lacking in the structural equation modeling (SEM) framework. We tackle the computational challenges associated with its SEM-implementation and propose a user-friendly free application for the L-APIM, which can be found at http://fgisteli.shinyapps.io/Shiny_LDD. As an illustration, we explore the actor and partner effects of positive relationship feelings on next day’s intimacy using 3-week diary data of 66 heterosexual couples.
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