Marginal maximum likelihood estimation of item parameters: Application of an EM algorithm |
| |
Authors: | R. Darrell Bock Murray Aitkin |
| |
Affiliation: | (1) Department of Behavioral Sciences, The University of Chicago, 5848 South University Avenue, 60637 Chicago, Illinois;(2) University of Lancaster, UK |
| |
Abstract: | Maximum likelihood estimation of item parameters in the marginal distribution, integrating over the distribution of ability, becomes practical when computing procedures based on an EM algorithm are used. By characterizing the ability distribution empirically, arbitrary assumptions about its form are avoided. The Em procedure is shown to apply to general item-response models lacking simple sufficient statistics for ability. This includes models with more than one latent dimension.Supported in part by NSF grant BNS 7912417 to the University of Chicago and by SSRC (UK) grant HR6132 to the University of Lancaster.We are indebted to Mark Reiser and Robert Gibbons for computer programming. David Thissen clarified a number of points in an earlier draft. |
| |
Keywords: | estimation of item parameters EM algorithm item analysis latent trait dichotomous factor analysis Law School Aptitude Test (LSAT) |
本文献已被 SpringerLink 等数据库收录! |