Internal Function for Multinomial Regression in Mplus

Usage

.mplusMultinomial(
  dv,
  iv,
  data,
  idvar = "",
  integration = 1000,
  processors = 2,
  OR = TRUE,
  pairwise = TRUE,
  ...
)

Arguments

dv: A character string with the variable name for the dependent (outcome) variable.
iv: A character vector with the variable name(s) for the independent (predictor/explanatory) variable(s).
data: A dataset.
idvar: Optional. A character string indicating the name of the ID variable. Not currently used but may be used in future.
integration: An integer indicating the number of Monte Carlo integration points to use. Defaults to 1000.
processors: An integer indicating the number of processors to use. Passed to Mplus. Defaults to 2.
OR: A logical value whether odds ratios should be returned. Defaults to TRUE.
pairwise: A logical value indicating whether all pairwise tests should be computed. Defaults to TRUE.
...: Additional arguments passed to mplusModeler().

Value

A list of results and Mplus model object.

Author

Joshua F. Wiley jwiley.psych@gmail.com

Examples

if (FALSE) { # \dontrun{

set.seed(1234)
tmpd <- data.frame(
  x1 = rnorm(200),
  x2 = rnorm(200),
  x3 = cut(rnorm(200),
           breaks = c(-Inf, -.7, .7, Inf),
           labels = c("a", "b", "c")))
tmpd$y <- cut(rnorm(200, sd = 2) + tmpd$x1 + tmpd$x2 + I(tmpd$x3 == "b"),
              breaks = c(-Inf, -.5, 1, Inf),
              labels = c("L", "M", "H"))

tmpres <- MplusAutomation:::.mplusMultinomial(
  dv = "y",
  iv = c("x1", "x2"),
  data = tmpd,
  pairwise = TRUE)
tmpres2 <- MplusAutomation:::.mplusMultinomial(
  dv = "y",
  iv = c("x1", "x2"),
  data = tmpd,
  pairwise = FALSE)
tmpres3 <- MplusAutomation:::.mplusMultinomial(
  dv = "y",
  iv = c("x1@0", "x2@0"),
  data = tmpd,
  pairwise = FALSE)

} # }