mixtureSummaryTable: Create a summary table of Mplus mixture models

Description

Creates a summary table of model fit statistics and relevant diagnostic information for a list of mixture models. Default statistics reported are in line with published guidelines (see Jung & Wickrama, 2008; Nylund et al., 2007): c("Title", "Classes", "Warnings", "AIC", "BIC", "aBIC", "Entropy", "T11_VLMR_PValue", "T11_LMR_PValue", "BLRT_PValue", "min_N", "max_N", "min_prob", "max_prob"). The table is customizable using the keepCols parameter, which is passed through to SummaryTable.

Usage

mixtureSummaryTable(
  modelList,
  keepCols = c("Title", "Classes", "Warnings", "AIC", "BIC", "aBIC", "Entropy",
    "T11_VLMR_PValue", "T11_LMR_PValue", "BLRT_PValue", "min_N", "max_N", "min_prob",
    "max_prob"),
  sortBy = NULL,
  ...
)

Value

An object of class data.frame.

Arguments

modelList: A list of models returned from the extractModelSummaries function.
keepCols: A vector of character strings indicating which columns/variables to display in the summary. Only columns included in this list will be displayed (all others excluded). By default, keepCols is: c("Title", "Classes", "Warnings", "AIC", "BIC", "aBIC","Entropy", "T11_VLMR_PValue", "T11_LMR_PValue", "BLRT_PValue", "min_N", "max_N", "min_prob", "max_prob").
sortBy: Field name (as character string) by which to sort the table. Typically an information criterion (e.g., "AIC" or "BIC") is used to sort the table. Defaults to "AICC". Set to NULL by default, so the table is ordered by increasing number of classes.
...: Arguments passed to SummaryTable.

Author

Caspar J. van Lissa

Examples

Run this code

if (FALSE) {
res <- createMixtures(classes = 1:2, filename_stem = "iris", rdata = iris,
               OUTPUT = "tech11 tech14;",
               run = 1L)
mixtureSummaryTable(res)
}