Quantitative Psychology Research (eBook, PDF)

The 78th Annual Meeting of the Psychometric Society
Redaktion: Millsap, Roger E.; Wang, Wen-Chung; Ark, L. Andries van der; Bolt, Daniel M.

• Format: PDF

Produktbeschreibung

The 78th Annual Meeting of the Psychometric Society (IMPS) builds on the Psychometric Society's mission to share quantitative methods relevant to psychology. The chapters of this volume present cutting-edge work in the field. Topics 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 in the social sciences who use quantitative methods. Prior knowledge of statistical methods is recommended. The 78th annual meeting took place in Arnhem, The Netherlands between July 22nd and 26th, 2013. The previous volume to showcase work from the Psychometric Society's Meeting is New Developments in Quantitative Psychology: Presentations from the 77th Annual Psychometric Society Meeting (Springer, 2014).

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Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 486
• Erscheinungstermin: 26. November 2014
• Englisch
• ISBN-13: 9783319075037
• Artikelnr.: 43793684

Autorenporträt

The Editors of this volume represent the Psychometric Society's 78th Annual International Meeting and the journal Psychometrika.

Inhaltsangabe

An empirical assessment of Guttman's Lambda 4 reliability coefficient.- Partitioning variance into constituents in multiple regression models: Commonality analysis.- Thurstonian item response theory and an application to attitude items.- Mediation analysis for ordinal outcome variables.- MTP2 and partial correlations in monotone higher-order factor models.- An option-based partial credit item response model.- What do you mean by a difficult item, On the interpretation of the difficulty parameter in a Rasch model.- Vertical comparison using reference sets.