This is a low level fitting function, for SEMSummary.
SEMSummary.fit(
formula,
data,
use = c("fiml", "pairwise.complete.obs", "complete.obs")
)A list with S3 class “SEMSummary”
A character vector containing the variable names.
An integer vector of the length of each variable used (this includes available and missing data).
An integer vector of the number of missing values in each variable.
A vector of the arithmetic means of each variable (on complete data).
A numeric vector of the standard deviations of each variable (on complete data).
The numeric covariance matrix for all variables.
The numeric correlation matrix for all variables.
A numeric matrix giving the percentage (technically decimal) of information available for each pairwise covariance/correlation.
The two-sided p values for the correlation matrix. Pairwise present N used to calculate degrees of freedom.
A formula of the variables to be used in the analysis. See the ‘details’ section for more information.
A data frame, matrix, or list containing the variables used in the formula. This is a required argument.
A character vector of how to handle missing data. Defaults to “fiml”.
SEMSummary