SEMSummary.fit: Summary Statistics for a SEM Analysis
In JWiley/JWileymisc: Miscellaneous Utilities and Functions

SEMSummary.fit

R Documentation

Summary Statistics for a SEM Analysis

This is a low level fitting function, for SEMSummary.

SEMSummary.fit(
  formula,
  data,
  use = c("fiml", "pairwise.complete.obs", "complete.obs")
)

`formula`	A formula of the variables to be used in the analysis. See the ‘details’ section for more information.
`data`	A data frame, matrix, or list containing the variables used in the formula. This is a required argument.
`use`	A character vector of how to handle missing data. Defaults to “fiml”.

A list with S3 class “SEMSummary”

`names`	A character vector containing the variable names.
`n`	An integer vector of the length of each variable used (this includes available and missing data).
`nmissing`	An integer vector of the number of missing values in each variable.
`mu`	A vector of the arithmetic means of each variable (on complete data).
`stdev`	A numeric vector of the standard deviations of each variable (on complete data).
`Sigma`	The numeric covariance matrix for all variables.
`sSigma`	The numeric correlation matrix for all variables.
`coverage`	A numeric matrix giving the percentage (technically decimal) of information available for each pairwise covariance/correlation.
`pvalue`	The two-sided p values for the correlation matrix. Pairwise present N used to calculate degrees of freedom.