Group iterative multiple model estimation
This package contains functions to identify group- and individual-level structural equation models.
Researchers across varied domains gather multivariate data for each individual unit of study
across multiple occasions of measurement. Generally referred to as time series
(or in the social sciences, intensive longitudinal) data, examples include
psychophysiological processes such as neuroimaging and heart rate variability,
daily diary studies, and observational coding of social interactions among dyads.
A primary goal for acquiring these data is to understand temporal processes.
The gimme package contains several functions for use with these data.
These functions include
gimmeSEM, which provides both group-
and individual-level results by looking across individuals for patterns of
relations among variables. A function that provides group-level results,
aggSEM, is included, as well as a function that provides
indSEM. The major functions within the gimme package all require the
user to specify the directory containing the data and a directory for output to be stored.
Stephanie Lane [aut, cre, trl],
Kathleen Gates [aut],
Peter Molenaar [aut],
Michael Hallquist [ctb],
Hallie Pike [ctb] Maintainer: Stephanie Lane firstname.lastname@example.org