LEADER 03958nam 22006375 450 001 9910300158403321 005 20220413191039.0 010 $a3-319-05536-4 024 7 $a10.1007/978-3-319-05536-7 035 $a(CKB)3710000000118071 035 $a(EBL)1731057 035 $a(OCoLC)885122249 035 $a(SSID)ssj0001216370 035 $a(PQKBManifestationID)11728717 035 $a(PQKBTitleCode)TC0001216370 035 $a(PQKBWorkID)11189384 035 $a(PQKB)10546077 035 $a(MiAaPQ)EBC1731057 035 $a(DE-He213)978-3-319-05536-7 035 $a(PPN)178780863 035 $a(EXLCZ)993710000000118071 100 $a20140524d2014 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aPerson-centered methods $eConfigural Frequency Analysis (CFA) and other methods for the analysis of contingency tables /$fby Mark Stemmler 205 $a1st ed. 2014. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2014. 215 $a1 online resource (94 p.) 225 1 $aSpringerBriefs in Statistics,$x2191-544X 300 $aDescription based upon print version of record. 311 $a1-322-03930-5 311 $a3-319-05535-6 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aIntroducing 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. 330 $aThis book takes an easy-to-understand look at the statistical approach called the person-centered method. Instead of analyzing means, variances and covariances of scale scores as in the common variable-centered approach, the person-centered approach analyzes persons or objects grouped according to their characteristic patterns or configurations in contingency tables. The main focus of the book will be on Configural Frequency Analysis (CFA; Lienert and Krauth, 1975) which is a statistical method that looks for over and under-frequented cells or patterns. Over frequented means that the observations in this cell or configuration are observed more often than expected, under-frequented means that this cell or configuration is observed less often than expected. In CFA a pattern or configuration that contains more observed cases than expected is called a type; similarly, a pattern or configuration that is less observed than expected are called an antitype. CFA is similar to log-linear modeling. In log-linear modeling the goal is to come up with a fitting model including all important variables. Instead of fitting a model, CFA looks at the significant residuals of a log-linear model. The book describes the use of an R-package called confreq (derived from Configural Frequency Analysis). The use of the software package is described and demonstrated with data examples. 410 0$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 $a519.54 700 $aStemmler$b Mark$4aut$4http://id.loc.gov/vocabulary/relators/aut$0721626 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910300158403321 996 $aPerson-centered methods$91410265 997 $aUNINA