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＜電子ブック＞
New Developments in Quantitative Psychology : Presentations from the 77th Annual Psychometric Society Meeting / edited by Roger E. Millsap, L. Andries van der Ark, Daniel M. Bolt, Carol M. Woods
(Springer Proceedings in Mathematics & Statistics. ISSN:21941017 ; 66)

版	1st ed. 2013.
出版者	(New York, NY : Springer New York : Imprint: Springer)
出版年	2013
本文言語	英語
大きさ	IX, 506 p. 107 illus., 44 illus. in color : online resource
著者標目	Millsap, Roger E editor van der Ark, L. Andries editor Bolt, Daniel M editor Woods, Carol M editor SpringerLink (Online service)
件　名	LCSH:Social sciences -- Statistical methods  全ての件名で検索 LCSH:Psychometrics LCSH:Psychology -- Methodology  全ての件名で検索 FREE:Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy FREE:Psychometrics FREE:Psychological Methods
一般注記	Preface -- The Effect of Response Model Misspecification and Uncertainty on the Psychometric Properties of Estimates -- Heterogeneous Populations and Multistage Test Design -- Backmatter The 77th Annual International Meeting of the Psychometric Society (IMPS) brought together quantitative researchers who focus on methods relevant to psychology.  The conference included workshops, invited talks by well-known scholars, and presentations of submitted papers and posters. It was hosted by the University of Nebraska-Lincoln and took place between the 9th and 12th of July, 2012. The chapters of this volume are based on presentations from the meeting and reflect the latest work in the field.   Topics with a primarily measurement focus include studies of item response theory, computerized adaptive testing, cognitive diagnostic modeling, and psychological scaling.  Additional psychometric topics relate to structural equation modeling, factor analysis, causal modeling, mediation, missing data methods, and longitudinal data analysis, among others.   The papers in this volume will be especially useful for researchers (graduate students and other quantitative researchers) in thesocial sciences who use quantitative methods, particularly psychologists.  Most readers will benefit from some prior knowledge of statistical methods in reading the chapters HTTP:URL=https://doi.org/10.1007/978-1-4614-9348-8

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