gimme (version 0.1-7)

indSEM: Individual-level structural equation model search.

Description

This function identifies structural equation models for each individual. It does not utilize any shared information from the sample.

Usage

indSEM(data   = "", out    = "", sep    = "", header = , ar     = TRUE, plot   = TRUE, paths  = NULL)

Arguments

data

The path to the directory where the data files are located. Each file must contain one matrix for each individual containing a T (time) by p (number of variables) matrix where the columns represent variables and the rows represent time.

out

The path to the directory where the results will be stored. This directory must be generated by the user prior to running the function.

sep

The spacing of the data files. "" indicates space-delimited, "/t" indicates tab-delimited, "," indicates comma delimited.

header

Logical. Indicate TRUE for data files with a header.

ar

Logical. If TRUE, begins search for individual models with autoregressive (AR) paths open. Defaults to TRUE.

plot

Logical. If TRUE, graphs depicting relations among variables of interest will automatically be created. Defaults to TRUE. For individual-level plots, red paths represent positive weights and blue paths represent negative weights.

paths

lavaan-style syntax containing paths with which to begin model estimation. That is, Y~X indicates that Y is regressed on X, or X predicts Y. If no header is used, then variables should be referred to with V followed (with no separation) by the column number. If a header is used, variables should be referred to using variable names. To reference lag variables, "lag" should be added to the end of the variable name with no separation. Defaults to NULL.

Details

In main output directory:

• indivPathEstimates Contains estimate, standard error, p-value, and z-value for each path for each individual
• summaryFit Contains model fit information for individual-level models.
• summaryPathCountMatrix Contains counts of total number of paths, both contemporaneous and lagged, estimated for the sample. The row variable is the outcome and the column variable is the predictor variable.
• summaryPathCounts Contains summary count information for paths identified at the individual-level.
• summaryPathsPlot Contains counts of total number of paths, both contemporaneous and lagged, estimated for the sample. The row variable is the outcome and the column variable is the predictor variable.

In individual output directory (where id represents the original file name for each individual):

• idBetas Contains individual-level estimates of each path for each individual.
• idStdErrors Contains individual-level standard errors for each path for each individual.
• idPlot Contains individual-level plots. Red paths represent positive weights and blue paths represent negative weights.

Examples

 ## Not run: 
# indSEM(data   = "C:/data100",
#        out    = "C:/data100_indSEM_out",
#        sep    = ",",
#        header = FALSE,
#        ar     = TRUE,
#        plot   = TRUE,
#        paths  = NULL)
#  ## End(Not run)