sim.categoric {MonteCarloSEM}

This function simulates (generates) categorical data sets by a given Confirmatory Factor Analysis model.

Description

Based on a given Confirmatory Factor Analysis model, this function simulates data sets. In each data file, the first column shows sample numbers. The second and other columns show actual simulated data sets for each item. If the model has 2 factors and each factor has 3 items, for example, column names will be something like "ID, F1_x1, F1_x2, F1_x3, F2_x1, F2_x2, F2_x3". On the other hand, the number of rows shows the sample number of the data. Besides, there will be two more files saved in the folder. First of them is "Model_Info.dat". This file includes factor correlation and factor loading matrices. The second is "Data_List.dat". The file contains the names of the data sets which were generated.

Usage

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

Arguments

nd

Number of the data set, an integer.

ss

Sample Size, an integer and larger than 10.

fcors

The factor correlation matrix, a symmetric matrix. If one-factor model is used this should be matrix(1,1,1).

loading

The factor loading matrix. The column represents factors and non-zero rows represent the number of items under each factor.

f.loc

File location. Generated data sets will be saved at the user-defined location.

threshold

The threshold values.

cont

TRUE or FALSE: Indicating whether original continuous data will be saved or not.

Author(s)

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 categories

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