MonteCarloSEM (version 2.0.0)

sim.categoric: Simulates Categorical Data Sets Based on a Structural Equation Model (SEM).

Description

This function generates categorical data sets from a specified SEM. The simulated data are organized such that the first column represents case identifiers, while the subsequent columns contain the simulated item responses. For example, in a model with two factors and three items per factor, the column labels will follow the format: "ID, F1_x1, F1_x2, F1_x3, F2_x1, F2_x2, F2_x3". The number of rows corresponds to the sample number of the data. In addition to the generated data sets, two supplementary files are also saved: (1) "Model_Info.dat" — containing the factor correlation and factor loading matrices (2) "Data_List.dat" — listing the names of all generated data files.

Usage

sim.categoric(
  nd = 10,
  ss = 100,
  fcors,
  loading,
  f.loc,
  threshold,
  cont = "FALSE"
)

Arguments

nd

An integer, the number of data sets to be generated.

ss

An integer, the sample size per data set (must be greater than 10).

fcors

The factor correlation matrix, which must be symmetric. For one-factor models, this should be "matrix(1,1,1)".

loading

The factor loading matrix. Columns correspond to factors, while non-zero rows specify the number of items associated with each factor.

f.loc

File path indicating the directory where the generated data sets will be saved.

threshold

Threshold values used to categorize continuous simulated data.

cont

Logical: If TRUE, the original continuous data sets are also saved in addition to the categorical versions.

Author

Fatih Orçan

Examples

fc<-fcors.value(nf=3, cors=c(1,.5,.6,.5,1,.4,.6,.4,1))
fl<-loading.value(nf=3, fl.loads=c(.5,.5,.5,0,0,0,0,0,0,0,0,.6,.6,.6,0,0,0,0,0,0,0,0,.4,.4))
tres<-c(-Inf, -1.645, -.643, .643, 1.645, Inf) # Five response categories

sim.categoric(nd=100,ss=100, fcors=fc,loading=fl, f.loc=tempdir(), threshold = tres)