首页 | 本学科首页   官方微博 | 高级检索  
     


Estimating latent distributions
Authors:Dr. Robert J. Mislevy
Affiliation:(1) National Opinion Research Center, USA;(2) Educational Testing Service, 08540 Princeton, N.J.
Abstract:Consider vectors of item responses obtained from a sample of subjects from a population in which abilitytheta is distributed with densityg(thetaVerbaragr), where theagr are unknown parameters. Assuming the responses depend ontheta through a fully specified item response model, this paper presents maximum likelihood equations for the estimation of the population parameters directly from the observed responses; i.e., without estimating an ability parameter for each subject. Also provided are asymptotic standard errors and tests of fit, computing approximations, and details of four special cases: a non-parametric approximation, a normal solution, a resolution of normal components, and a beta-binomial solution.The author would like to thank R. Darrell Bock for his comments, suggestions, and encouragement during the course of this work.
Keywords:latent distributions  maximum likelihood  EM algorithm  empirical Bayes estimation  Gaussian resolution  beta-binomial model  item response theory
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号