Reference : An iterative maximum a posteriori estimation of proficiency level to detect multiple loc...

	Document type :	Scientific journals : Article
	Discipline(s) :	Physical, chemical, mathematical & earth Sciences : Mathematics
	To cite this reference:	http://hdl.handle.net/2268/31760

Title :	An iterative maximum a posteriori estimation of proficiency level to detect multiple local likelihood maxima
Language :	English
Alternative title :	[fr] Estimation itérative de l'habileté par maximum a posteriori pour détecter les les maxima de vraisemblance locaux
Author, co-author :	Magis, David [Université de Liège - ULg > Département de mathématique > Statistique mathématique >]
	Raîche, Gilles [Université du Québec à Montréal > Education et pédagogie > > >]
Publication date :	2010
Journal title :	Applied Psychological Measurement
Publisher :	SAGE Publications
Volume :	34
Pages :	75-90
Audience :	International
ISSN :	0146-6216
Keywords :	[en] maximum likelihood ; Bayesian estimation ; iterative MAP
Abstract :	[en] In this article the authors focus on the issue of the nonuniqueness of the maximum likelihood (ML) estimator of proficiency level in item response theory (with special attention to logistic models). The usual maximum a posteriori (MAP) method offers a good alternative within that framework; however, this article highlights some drawbacks of its use. The authors then propose an iteratively based MAP estimator (IMAP), which can be useful in detecting multiple local likelihood maxima. The efficiency of the IMAP estimator is studied and is compared to the ML and MAP methods by means of a simulation study.
Permalink :	http://hdl.handle.net/2268/31760

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	Fulltext file(s): File Commentary Version Size Access Restricted access Applied Psychological Measurement 34 (2010) 75-90.pdf Publisher postprint 241.59 kB Request copy

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