KB36_t

<p>The data set contains item parameters estimates following a 3PL model for two 36-items tests forms, 
rescaled using mean-sigma method's A and B using all common items except item 27. This data has been described and analized by Kolen and Brennan (2004), Table 6.8.</p>

datasets

Contains functions to perform various models and
methods for test equating. It currently implements the traditional
mean, linear and equipercentile equating methods. Both IRT observed-score
and true-score equating are also supported, as well as the mean-mean,
mean-sigma, Haebara and Stocking-Lord IRT linking methods.
It also supports newest methods such that local equating, kernel
equating (using Gaussian, logistic, Epanechnikov, uniform and adaptive
kernels) with presmoothing, and IRT parameter linking methods based on
asymmetric item characteristic functions. Functions to obtain both
standard error of equating (SEE) and standard error of equating differences
between two equating functions (SEED) are also implemented for the kernel method of
equating.

Jorge Gonzalez

SNSequate

Standard and Nonstandard Statistical Models and Methods for Test
Equating

Daniel Leon Acuna

KB36_t function

<p>A dataframe where each column represent item parameter estimates of forms <code>X</code> and <code>Y</code>, with their respective p-values.</p>

KB36_t: Data on two 36-items test forms

Description

Usage

Arguments

Format

References

See Also

Examples