Document Detail

Some exact tests for manifest properties of latent trait models.
MedLine Citation:
PMID:  21562625     Owner:  NLM     Status:  Publisher    
Item response theory is one of the modern test theories with applications in educational and psychological testing. Recent developments made it possible to characterize some desired properties in terms of a collection of manifest ones, so that hypothesis tests on these traits can, in principle, be performed. But the existing test methodology is based on asymptotic approximation, which is impractical in most applications since the required sample sizes are often unrealistically huge. To overcome this problem, a class of tests is proposed for making exact statistical inference about four manifest properties: covariances given the sum are non-positive (CSN), manifest monotonicity (MM), conditional association (CA), and vanishing conditional dependence (VCD). One major advantage is that these exact tests do not require large sample sizes. As a result, tests for CSN and MM can be routinely performed in empirical studies. For testing CA and VCD, the exact methods are still impractical in most applications, due to the unusually large number of parameters to be tested. However, exact methods are still derived for them as an exploration toward practicality. Some numerical examples with applications of the exact tests for CSN and MM are provided.
Jan G De Gooijer; Ao Yuan
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Publication Detail:
Journal Detail:
Title:  Computational statistics & data analysis     Volume:  55     ISSN:  0167-9473     ISO Abbreviation:  -     Publication Date:  2011 Jan 
Date Detail:
Created Date:  2011-5-12     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  100960938     Medline TA:  Comput Stat Data Anal     Country:  -    
Other Details:
Languages:  ENG     Pagination:  34-44     Citation Subset:  -    
Department of Quantitative Economics, University of Amsterdam, Roetersstraat 11, 1018 WB Amsterdam, The Netherlands.
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Grant Support
G12 RR003048-21A1//NCRR NIH HHS

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