wpermut: generate permutated weight matrices

In christinehohensinn/parAL: Goodness-of-fit of the user-defined weight matrix of the linear logistic test model

Description

generate weight matrices that permutate rows from the original weight matrix

Usage

Wpermut(datmat, weightmat, repl = 100, keepmat = FALSE)

Arguments

datmat	data file
weightmat	original weight matrix
repl	number of weight matrices that are generated
keepmat	if TRUE, the generated random weight matrices are kept in an three-dimensional array

Details

The original weight matrix is taken and new weight matrices are generated by permutating the rows of the original matrix. The permutations are drawn randomly. Duplicated permutations are eliminated - thus the user-defined number of replications can deviate from the number of generated weight matrices. For each generated weight matrix, an LLTM is estimated using the function DRM of the R package pcIRT. A Rasch model is estimated for the original data set using the function DRM from pcIRT. The item parameters estimated by the Rasch model are correlated with the item parameters reconstructed from the parameters estimated by the LLTM.

Value

conv	convergence of the estimated LLTMs of the generated weight matrices
npermut	number of generated weight matrices
nchange	matrix with the frequencies of the number of rows that were changed in the generated weight matrices
hchange	vector with the number of changed rows for each permutation
raschpar	estimated Rasch model item parameters for the original data set
lltmpar	item parameters reconstructed from the estimated parameters of the LLTM of the generated weight matrices
corlr	correlation of the re-constructed item parameters by the LLTM and the estimated item parameters of the original Rasch model
sumcorlr	short summary descriptive statistics of the correlations
randommat	array containing the generated weight matrices (if argument keepmat is set TRUE)

Author(s)

Christine Hohensinn

References

Baghaei, P. & Hohensinn, C. (submitted). A Method of Q-Matrix Validation for the Linear Logistic Test Model.

Fischer, G. H. (1973). The linear logistic test model as an instrument in educational research. Acta Psychologica, 37, 359-374.

Examples

#generate three permutated weight matrices for example data set
data(exampledata)
data(exampleweight)

Wpermut(exdat, orig.weight, repl=3)

christinehohensinn/parAL documentation built on May 13, 2019, 7 p.m.