Evaluation of Item Fit With Output From the EM Algorithm: RMSD Index Based on Posterior Expectations.

ABSTRACT: In item response theory modeling, item fit analysis using posterior expectations, otherwise known as pseudocounts, has many advantages. They are readily obtained from the E-step output of the Bock-Aitkin Expectation-Maximization (EM) algorithm and continue to function as a basis of evaluating model fit, even when missing data are present. This paper aimed to improve the interpretability of the root mean squared deviation (RMSD) index based on posterior expectations. In Study 1, we assessed its performance using two approaches. First, we employed the poor person's posterior predictive model checking (PP-PPMC) to compute their significance levels. The resulting Type I error was generally controlled below the nominal level, but power noticeably declined with smaller sample sizes and shorter t

SUBMITTER: Kim YK 

PROVIDER: S-EPMC12496452 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature