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A Direct Bayesian Estimation of Reliability

Yasuharu Okamoto

Behaviormetrika, 2013, 40, 149-168

 

Abstract

Bayesian estimation of reliability by MCMC is proposed as an alternative to

coefficient alpha, regarded as a classic method of estimating reliability.

However, coefficient alpha is derived from a structural factor model,

various kinds of which are used in modern data analysis, e.g., SEM,

sometimes used to analyze reliability. SEM emphasizes covariances

to analyze categorical items that are estimated by polychoric correlations.

The methods proposed in this study directly apply the MCMC algorithm to

individual examinees responses. Thus, covariances are not estimated but

implicitly represented by factor models. For categorical items, models for

continuous items are modified and applied based on an ordinal probit regression.

The performances of the proposed models and algorithms are investigated by

simulations and successful results are obtained.

 

For Full Text, visit the website <https://www.jstage.jst.go.jp/article/bhmk/40/2/40_149/_article>

 

A program to analyze continuous items is prepared at this website (in Japanese).

A program to analyze categorical items is prepared at this website (in Japanese).

 

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