Rasch.PCA.ltm: Rasch Residual Principal Component Analysis

In changxiulee/BayesianRasch: Bayesian Rasch Modeling

Description

This is for unidimensionality assumption check. If the data is unidimensional, the eigenvalue for the first constrast should be less than 2. However, when the eigenvalue is more than 2, it can either indicate a local change in intensity or the multidimensionality. To know this, use the item.selection method. Please note that this function utlized ltm's MMLE to estimate the parameter. It should be almost identical to the result from Rasch.PCA.Bayes but faster.

Usage

Rasch.PCA.ltm(data, item)

Arguments

data	A data frame containing the data
item	Item to be included in Rasch

changxiulee/BayesianRasch documentation built on Nov. 18, 2019, 6:54 a.m.