generic_model {autoRasch}

Estimation of the generic form of the models

Description

This function computes the parameter estimates of the generic form of the models by using penalized JML estimation. It allows users to adjust the default settings of the estimation.

Usage

generic_model(X, init_par = c(), setting = c())

Arguments

X

Input dataset as matrix or data frame with ordinal responses (starting from 0); rows represent individuals, column represent items.

init_par

Initial values of the estimated parameters.

setting

Parameter settings which are listed in autoRaschOptions().

Details

In the discrimination parameters estimation, instead of estimating the discrimination parameters, we are estimating the natural logarithm of the parameters to avoid negative values, \alpha = exp(\gamma).

Value

X

The dataset that is used for estimation.

name

The name of each items in the dataset.

mt_vek

A vector of the highest response category as many as the number of items.

loglik

The log likelihood of the estimation.

objtype

Type of the model that is used.

delta

A vector of the DIF parameters of each items on each groups.

gamma

A vector of the natural logarithm of discrimination parameters of each items.

beta

A vector of the difficulty parameter of each items' categories (thresholds).

theta

A vector of the ability parameters of each individuals.