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＜電子ブック＞
Person-Centered Methods : Configural Frequency Analysis (CFA) and Other Methods for the Analysis of Contingency Tables / by Mark Stemmler
(SpringerBriefs in Statistics. ISSN:21915458)

版	1st ed. 2014.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2014
本文言語	英語
大きさ	VIII, 88 p. 18 illus., 2 illus. in color : online resource
著者標目	*Stemmler, Mark author SpringerLink (Online service)
件　名	LCSH:Social sciences -- Statistical methods  全ての件名で検索 LCSH:Statistics  FREE:Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy FREE:Statistical Theory and Methods FREE:Statistics
一般注記	Introducing Person-Centered Methods -- CFA Software -- Significance Testing in CFA -- CFA and Log-Linear Modeling -- Longitudinal CFA -- Other Person-Centered Methods Serving as Complimentary Tools to CFA -- CFA and its derivatives -- Glossary -- Index This book takes an easy-to-understand look at the statistical approach called the person-centered method. Instead of analyzing means, variances and covariances of scale scores as in the common variable-centered approach, the person-centered approach analyzes persons or objects grouped according to their characteristic patterns or configurations in contingency tables. The main focus of the book will be on Configural Frequency Analysis (CFA; Lienert and Krauth, 1975) which is a statistical method that looks for over and under-frequented cells or patterns. Over frequented means that the observations in this cell or configuration are observed more often than expected, under-frequented means that this cell or configuration is observed less often than expected. In CFA a pattern or configuration that contains more observed cases than expected is called a type; similarly, a pattern or configuration that is less observed than expected are called an antitype. CFA is similar to log-linear modeling. In log-linear modeling the goal is to come up with a fitting model including all important variables. Instead of fitting a model, CFA looks at the significant residuals of a log-linear model. The book describes the use of an R-package called confreq (derived from Configural Frequency Analysis). The use of the software package is described and demonstrated with data examples HTTP:URL=https://doi.org/10.1007/978-3-319-05536-7

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