15795482

Source:http://linkedlifedata.com/resource/pubmed/id/15795482

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Predicate	Object
rdf:type	pubmed:Citation
lifeskim:mentions	umls-concept:C0026336, umls-concept:C0150312, umls-concept:C0456148, umls-concept:C0549193, umls-concept:C0683312
pubmed:issue	2
pubmed:dateCreated	2005-3-29
pubmed:abstractText	A category with a frequency of zero is called a null category. When null categories are present in polytomous responses, then in the Rasch model for such responses, the thresholds that define the categories are inestimable with the commonly used joint maximum likelihood, marginal maximum likelihood, or standard conditional maximum likelihood estimation algorithms. The reason for this situation is that in principle, these estimation algorithms involve frequencies of each category. Andrich and Luo (2003) describe an algorithm in which the thresholds are reparameterized into their principal components and in which the estimate of any threshold is based on a function of the frequencies of all categories of the item rather than the frequency of a particular category. This algorithm works in the presence of null categories. However, in situations where the null categories are at the extremes of a set of categories, the estimates themselves can become too extreme. This paper describes a procedure in which the solution algorithm described by Andrich and Luo is further adapted in the presence of null categories by using their expected frequencies. The procedure is demonstrated with simulated and real data.
pubmed:language	eng
pubmed:journal	http://linkedlifedata.com/resource/pubmed/journal/101084377
pubmed:citationSubset	IM
pubmed:status	MEDLINE
pubmed:issn	1529-7713
pubmed:author	pubmed-author:AndrichDavidD, pubmed-author:LuoGuanzhongG
pubmed:issnType	Print
pubmed:volume	6
pubmed:owner	NLM
pubmed:authorsComplete	Y
pubmed:pagination	128-46
pubmed:dateRevised	2006-11-15
pubmed:meshHeading	pubmed-meshheading:15795482-Algorithms, pubmed-meshheading:15795482-Models, Statistical
pubmed:year	2005
pubmed:articleTitle	Estimating parameters in the Rasch model in the presence of null categories.
pubmed:affiliation	Research Division, Hong Kong Examinations and Assessment Authority, 130 Hennessy Road, Wan Chai, Hong Kong. gluo@hkeaa.edu.hk
pubmed:publicationType	Journal Article, Research Support, Non-U.S. Gov't