Automated Selection of Robust Individual-Level Structural Equation Models for Time Series Data

作者：Lane Stephanie T^*; Gates Kathleen M

来源：Structural Equation Modeling, 2017, 24(5): 768-782.

DOI：10.1080/10705511.2017.1309978

• structural equation modeling
• R
• time series

In order to analyze intensive longitudinal data collected across multiple individuals, researchers frequently have to decide between aggregating all individuals or analyzing each individual separately. This paper presents an R package, gimme, which allows for the automatic specification of individual-level structural equation models that combine group-, subgroup-, and individual-level information. This R package is a complement of the GIMME program currently available via a combination of MATLAB and LISREL. By capitalizing on the flexibility of R and the capabilities of the existing structural equation modeling package lavaan, gimme allows for the automated specification and estimation of group-, subgroup-, and individual-level relations in time series data from within a structural equation modeling framework. Applications include daily diary data as well as functional magnetic resonance imaging data.

• 出版日期2017