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Activity Number: 584
Type: Contributed
Date/Time: Wednesday, August 1, 2012 : 2:00 PM to 3:50 PM
Sponsor: Social Statistics Section
Abstract - #305580
Title: Newton-Type Algorithms for the Estimation of Item Response Theory Model
Author(s): Xinming An*+ and Yiu-Fai Yung
Companies: SAS Institute and SAS Institute
Address: 600 Research Dr, Cary, NC, 27513, United States
Keywords: item response theory ; Newton algorithm ; EM algorithm

In the field of item response theory, G-H quadrature based EM proposed by Bock and Aitkin (1981) has been widely recognized as the golden standard for model estimation because of its several appealing properties. However, these advantages are overshadowed by a number of important issues that has not been resolved successfully. Furthermore, recent developments in item factor analysis, for example, confirmatory analysis, also impair EM's advantages. During the last twenty years, statistical researches have been impacted dramatically by the advances in computational sciences. Thus it is important to apply these computational advances to Newton and EM type algorithms and re-evaluate their relative advantages. To this end, the focus of this research is to (1) propose some Newton type algorithms for item factor analysis; and (2) investigate the computational properties of these Newton type alg

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