LEADER 05522oam 2200637Ia 450 001 9910139367903321 005 20240116212010.0 010 $a1-282-55119-1 010 $a9786612551192 010 $a0-470-58333-9 010 $a0-470-58332-0 035 $a(CKB)2520000000006705 035 $a(EBL)495964 035 $a(OCoLC)587380836 035 $a(SSID)ssj0000366216 035 $a(PQKBManifestationID)11257546 035 $a(PQKBTitleCode)TC0000366216 035 $a(PQKBWorkID)10413961 035 $a(PQKB)10525870 035 $a(MiAaPQ)EBC495964 035 $a(EXLCZ)992520000000006705 100 $a20090803d2010 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aStatistics in the social sciences $ecurrent methodological developments /$fedited by Stanislav Kolenikov, Douglas Steinley, Lori Thombs 210 1$aHoboken, N.J. :$cWiley,$d2010. 210 4$dİ2010 215 $a1 online resource (xxii, 198 pages) $cillustrations 300 $aDescription based upon print version of record. 311 0 $a0-470-14874-8 320 $aIncludes bibliographical references and index. 327 $aStatistics in the Social Sciences: Current Methodological Developments; Contents; List of Figures; List of Tables; Preface; 1 Analysis of Correlation Structures: Current Status and Open Problems; 1.1 Introduction; 1.2 Correlation versus Covariance Structures; 1.3 Estimation and Model Testing; 1.3.1 Basic Asymptotic Theory; 1.3.2 Distribution of T Under Model Misspecification; 1.3.3 Distribution of T Under Weight Matrix Misspecification; 1.3.4 Estimation and Testing with Arbitrary Distributions; 1.3.5 Tests of Model Fit Under Distributional Misspecification 327 $a1.3.6 Scaled and Adjusted Statistics; 1.3.7 Normal Theory Estimation and Testing; 1.3.8 Elliptical Theory Estimation and Testing; 1.3.9 Heterogeneous Kurtosis Theory Estimation and Testing; 1.3.10 Least Squares Estimation and Testing; 1.4 Example; 1.5 Simulations; 1.5.1 Data; 1.5.2 Correlation Structure with ADF Estimation and Testing; 1.5.3 Correlation Structure with Robust Least Squares Methods; 1.6 Discussion; References; 2 Overview of Structural Equation Models and Recent Extensions; 2.1 Model Specification and Assumptions; 2.1.1 Illustration of Special Cases; 2.1.2 Modeling Steps 327 $a2.2 Multilevel SEM; 2.2.1 The Between-and-Within Specification; 2.2.2 Random Effects as Factors Specification; 2.2.3 Summary and Comparison; 2.3 Structural Equation Mixture Models; 2.3.1 The Model; 2.3.2 Estimation; 2.3.3 Sensitivity to Assumptions; 2.3.4 Direct and Indirect Applications; 2.3.5 Summary; 2.4 Item Response Models; 2.4.1 Categorical CFA; 2.4.2 CCFA Estimation; 2.4.3 Item Response Theory; 2.4.4 CCFA and IRT; 2.4.5 Advantages and Disadvantages; 2.5 Complex Samples and Sampling Weights; 2.5.1 Complex Samples and Their Features; 2.5.2 Probability (Sampling) Weights. 327 $a2.5.3 Violations of SEM Assumptions; 2.5.4 SEM Analysis Using Complex Samples with Unequal Probabilities of Selection; 2.5.5 Future Research; 2.6 Conclusion; References; 3 Order-Constrained Proximity Matrix Representations; 3.1 Introduction; 3.1.1 Proximity Matrix for Illustration: Agreement Among Supreme Court Justices; 3.2 Order-Constrained Ultrametrics; 3.2.1 The M-file ultrafnd_confit.m; 3.2.2 The M-file ultrafnd_confnd.m; 3.2.3 Representing an (Order-Constrained) Ultrametric; 3.2.4 Alternative (and Generalizable) Graphical Representation for an Ultrametric 327 $a3.2.5 Alternative View of Ultrametric Matrix Decomposition; 3.3 Ultrametric Extensions by Fitting Partitions Containing Contiguous Subsets; 3.3.1 Ordered Partition Generalizations; 3.4 Extensions to Additive Trees: Incorporating Centroid Metrics; References; 4 Multiobjective Multidimensional (City-Block) Scaling; 4.1 Introduction; 4.2 City-Block MDS; 4.3 Multiobjective City-Block MDS; 4.3.1 The Metric Multiobjective City-Block MDS Model; 4.3.2 The Nonmetric Multiobjective City-Block MDS Model; 4.4 Combinatorial Heuristic; 4.5 Numerical Examples; 4.5.1 Example 1; 4.5.2 Example 2; 4.6 Summary and Conclusions 330 $aA one-of-a-kind compilation of modern statistical methods designed to support and advance research across the social sciences Statistics in the Social Sciences: Current Methodological Developments presents new and exciting statistical methodologies to help advance research and data analysis across the many disciplines in the social sciences. Quantitative methods in various subfields, from psychology to economics, are under demand for constant development and refinement. This volume features invited overview papers, as well as original research presented at the Sixth Annual Wine 606 $aSocial sciences$xStatistical methods$vCongresses 606 $aStatistics$vCongresses 615 0$aSocial sciences$xStatistical methods 615 0$aStatistics 676 $a519.50243 701 $aKolenikov$b Stanislav$0614599 701 $aSteinley$b Douglas$0614600 701 $aThombs$b Lori A$0614601 712 12$aAnnual Winemiller Conference on Methodological Developments of Statistics in the Social Sciences$d(6th :$f2006 :$eUniversity of Missouri--Columbia) 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910139367903321 996 $aStatistics in the social sciences$91131689 997 $aUNINA