aMNLFA (version 1.1.2)

aMNLFA.object: aMNLFA object function

Description

This function creates an aMNLFA object based on user specifications to pass to aMNLFA functions.

Usage

aMNLFA.object(
  dir,
  mrdata,
  indicators = NULL,
  catindicators = NULL,
  countindicators = NULL,
  meanimpact = NULL,
  varimpact = NULL,
  measinvar = NULL,
  factors = NULL,
  time = NULL,
  auxiliary = NULL,
  ID = NULL,
  thresholds = NULL
)

Arguments

dir

The directory in which data, inputs, and outputs are to be stored. Must be supplied.

mrdata

The R dataframe containing the multiple-record dataset. Must be supplied.

indicators

The names of all indicators (items, observed variables) in the MNLFA.

catindicators

The list of indicators which are categorical. Defaults to NULL.

countindicators

The list of indicators which are count. Defaults to NULL.

meanimpact

The list of covariates (predictors) which may generate impact on the latent variable mean. Defaults to NULL.

varimpact

The list of covariates (predictors) which may generate impact on the latent variable variance. Defaults to NULL.

measinvar

The list of covariates (predictors) which may generate DIF. Defaults to NULL.

factors

The list of covariates which are categorical. Defaults to NULL.

time

The variable which indexes time (or multiple records within a single case). If left blank, assumes single-record data. Defaults to NULL.

auxiliary

The list of variables to be considered as auxiliary (i.e., retained in the dataset but not used in the analysis). Defaults to NULL.

ID

The variable which identifies cases. Defaults to NULL.

thresholds

A Boolean operator indicating whether to test for threshold DIF.

Examples

# NOT RUN {
 
# }
# NOT RUN {
 wd <- tempdir()
 first<-paste0(system.file(package='aMNLFA'),"/examplefiles")
 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)
 
# }
# NOT RUN {
 
# }