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).