IRTBEMM: Family of Bayesian EMM Algorithm for Item Response Models
Shaoyang Guo, Chanjin Zheng, Justin L. Kern · 2020
Applying the family of the Bayesian Expectation-Maximization-Maximization (BEMM) algorithm to estimate: (1) Three parameter logistic (3PL) model proposed by Birnbaum (1968, ISBN:9780201043105); (2) four parameter logistic (4PL) model proposed by Barton & Lord (1981) ; (3) one parameter logistic guessing (1PLG) and (4) one parameter logistic ability-based guessing (1PLAG) models proposed by San Martín et al (2006) . The BEMM family includes (1) the BEMM algorithm for 3PL model proposed by Guo & Zheng (2019) ; (2) the BEMM algorithm for 1PLG model and (3) the BEMM algorithm for 1PLAG model proposed by Guo, Wu, Zheng, & Chen (2021) ; (4) the BEMM algorithm for 4PL model proposed by Zheng, Guo, & Kern (2021) ; and (5) their maximum likelihood estimation versions proposed by Zheng, Meng, Guo, & Liu (2018) . Thus, both Bayesian modal estimates and maximum likelihood estimates are available.