DIMTEST Enhancements and Some Parametric IRT Asymptotics
Gao, Furong
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https://hdl.handle.net/2142/87416
Description
Title
DIMTEST Enhancements and Some Parametric IRT Asymptotics
Author(s)
Gao, Furong
Issue Date
1997
Doctoral Committee Chair(s)
William Stout
Department of Study
Statistics
Discipline
Statistics
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Statistics
Language
eng
Abstract
The joint consistency of item and ability parameter estimation remains a challenging problem in IRT parametric modeling. Although many simulation studies have been conducted on the item and ability parameter estimates obtained by joint maximum likelihood estimation which is implemented in LOGIST (Wingersky, Bartaon, & Lord, 1982) procedure, there is no analytical results about the asymptotic properties of these estimates in literature. A preliminary effort is made to joint consistently estimate the item and ability parameters using a new approach under some regularity conditions. It is shown that when uniformly consistent ability parameter estimates are available and used as the true ability values, consistent item parameter estimates exist in a subsequence of their MLE estimates assuming ability parameters are known.
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