aMNLFA.final: aMNLFA simultaneous model fitting function

In vtcole/aMNLFA: Automated Moderated Nonlinear Factor Analysis Using 'Mplus'

Description

This function generates the simultaneous aMNLFA model from all the initial inputs.

Usage

aMNLFA.final(
  input.object,
  mchoice = "actual",
  method = "BH",
  highest.category = TRUE,
  keepmean = FALSE
)

Arguments

input.object	The aMNLFA object (created using the aMNLFA.object function) which provides instructions for the function.
mchoice	String representing the method of determining the number of tests, denoted m. Options include "actual", which uses the number of effects actually tested in the round 2 model as m, and "ibc", which uses the maximum number of all possible tests – i.e., the number of items times the number of covariates. Defaults to "actual".
method	String representing the method of adjusting for multiple comparisons. Options include "bh", which invokes Benjamini-Hochberg correction with m defined using the mchoice parameter, and "bonferroni", which invokes a Bonferroni correction with m defined using the mchoice parameter. Defaults to "bh".
highest.category	Boolean. If threshold DIF is tested, should only the category with the highest value of the test statistic be used when adjusting p. values? Defaults to TRUE, which corresponds to the results from "threshold.highest" in the aMNLFA.prune() step. If FALSE, all threshold effects will be considered, even those below the maximum value for a given item, which corresponds to the "thresholds.all" option in the aMNLFA.prune() step.
keepmean	Boolean. If intercept or loading DIF are present, should the corresponding mean impact effect be retained? Defaults to FALSE.

Value

No return value. Generates a file entitled "round3calibration.inp", to be run in Mplus, in the directory specified in the aMNLFA.object.

Examples

 wd  <-  tempdir()
 first <- paste0(system.file(package='aMNLFA'),"/extdata")
 the.list  <-  list.files(first,full.names=TRUE)
 file.copy(the.list,wd,overwrite=TRUE)
   
 ob  <-  aMNLFA::aMNLFA.object(dir = wd, 
 mrdata = xstudy, 
 indicators = paste0("BIN_", 1:12),
 catindicators = paste0("BIN_", 1:12), 
 meanimpact = c("AGE", "GENDER", "STUDY"), 
 varimpact = c("AGE", "GENDER", "STUDY"), 
 measinvar = c("AGE", "GENDER", "STUDY"),
 factors = c("GENDER", "STUDY"),
 ID = "ID",
 thresholds = FALSE)
 
 aMNLFA.simultaneous(ob)

vtcole/aMNLFA documentation built on Nov. 7, 2021, 6:11 p.m.