LEADER 03638nam 22005295 450 001 996418253903316 005 20200813213322.0 010 $a3-030-49421-7 024 7 $a10.1007/978-3-030-49421-6 035 $a(CKB)4100000011384323 035 $a(DE-He213)978-3-030-49421-6 035 $a(MiAaPQ)EBC6301433 035 $a(PPN)250215608 035 $a(EXLCZ)994100000011384323 100 $a20200813d2020 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPerson-Centered Methods$b[electronic resource] $eConfigural Frequency Analysis (CFA) and Other Methods for the Analysis of Contingency Tables /$fby Mark Stemmler 205 $a2nd ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (X, 116 p. 29 illus., 5 illus. in color.) 225 1 $aSpringerBriefs in Statistics,$x2191-544X 311 $a3-030-49420-9 320 $aIncludes bibliographical references and index. 327 $a1. Introducing Person-Centered Methods -- 2. CFA Software -- 3. Significance Testing in CFA -- 4. CFA and Log-Linear Modeling -- 5. Longitudinal CFA -- 6. Other Person-Centered Methods Serving as Complimentary Tools for CFA -- 7. CFA and its Derivatives -- Glossary -- Index. 330 $aThis book offers a comprehensible overview of the statistical approach called the person-centered method. Instead of analyzing means, variances and covariances of scale scores as in the common variable-centered approach, the person-centered approach analyzes persons or objects grouped according to their characteristic patterns or configurations in contingency tables. This second edition explores the relationship between two statistical methods: log-linear modeling (LLM) and configural frequency analysis (CFA). Both methods compare expected frequencies with observed frequencies. However, while LLM searches for the underlying dependencies of the involved variables in the data (model-fitting), CFA examines significant residuals in non-fitting models. New developments in the second edition include: Configural Mediation Models, CFA with covariates, moderator CFA, and CFA modeling branches in tree-based methods. The new developments enable the use of categorical together with continuous variables, which makes CFA a very powerful statistical tool. This new edition continues to utilize R-package confreq (derived from Configural Frequency Analysis), much updated since the first edition and newly adjusted to the new R base program 4.0. An electronic supplement is now available with 18 R-scripts and many datasets. 410 0$aSpringerBriefs in Statistics,$x2191-544X 606 $aStatistics  606 $aStatistics for Social Sciences, Humanities, Law$3https://scigraph.springernature.com/ontologies/product-market-codes/S17040 606 $aStatistical Theory and Methods$3https://scigraph.springernature.com/ontologies/product-market-codes/S11001 606 $aStatistics, general$3https://scigraph.springernature.com/ontologies/product-market-codes/S0000X 615 0$aStatistics . 615 14$aStatistics for Social Sciences, Humanities, Law. 615 24$aStatistical Theory and Methods. 615 24$aStatistics, general. 676 $a519.5 700 $aStemmler$b Mark$4aut$4http://id.loc.gov/vocabulary/relators/aut$0721626 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996418253903316 996 $aPerson-centered methods$91410265 997 $aUNISA