Automated Selection of Robust Individual-Level Structural Equation Models for Time Series Data. Issue 5 (3rd September 2017)

• Record Type: Journal Article
• Authors: Lane, Stephanie T.; Gates, Kathleen M.
• Is Part Of: Structural equation modeling. Volume 24:Issue 5(2017)
• Page Start: 768
• Page End: 782
• Publication Date: 2017-09-03
• Subjects: structural equation modeling -- R -- time series; Multivariate analysis -- Periodicals; Social sciences -- Statistical methods -- Periodicals; 519.535
• DOI: 10.1080/10705511.2017.1309978
• Languages: English
• ISSNs: 1070-5511

Abstract

Abstract : 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.