SEMSummary.fit {JWileymisc}

Summary Statistics for a SEM Analysis

Description

This is a low level fitting function, for SEMSummary.

Usage

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

Arguments

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”.

Value

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.

See Also

SEMSummary