LEADER 03513nam 22005895 450 001 9910897991003321 005 20250325165625.0 010 $a9783031563188 010 $a3031563182 024 7 $a10.1007/978-3-031-56318-8 035 $a(CKB)36383084800041 035 $a(MiAaPQ)EBC31735068 035 $a(Au-PeEL)EBL31735068 035 $a(DE-He213)978-3-031-56318-8 035 $a(EXLCZ)9936383084800041 100 $a20241021d2024 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDependent Data in Social Sciences Research $eForms, Issues, and Methods of Analysis /$fedited by Mark Stemmler, Wolfgang Wiedermann, Francis L. Huang 205 $a2nd ed. 2024. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2024. 215 $a1 online resource (785 pages) 311 08$a9783031563171 311 08$a3031563174 327 $aGrowth Curve Modeling -- Directional Dependence -- Dydatic Data Modeling -- Item Response Modeling -- Other Methods for the Analyses of Dependent Data. 330 $aThis second edition presents a variety of up-to-date statistical issues with regard to dependent or longitudinal data such as continuous time modeling, growth curve modeling, dynamic modeling, network analysis, Bayesian network analysis, directional dependence, multilevel analysis, item response modeling (IRT), estimation of missing data of longitudinal data and other methods for the analysis of dependent data (e.g., configural frequency analysis, ecological momentary assessment, and unobserved within-group individual differences). It presents contributions on handling data in which the postulate of independence in the data matrix is violated. When this postulate is violated and when the methods assuming independence are still applied, the estimated parameters are likely to be biased, and statistical decisions are very likely to be incorrect. Problems associated with dependence in data have been known for a long time, and led to the development of tailored methods for the analysis of dependent data in various areas of statistical analysis. In addition, R-scripts to recapture the presented content are provided. Researchers and graduate students in the social and behavioral sciences, education, econometrics, mathematics, biology, physics and medicine will find this up-to-date overview of modern statistical approaches for dealing with problems related to dependent data particularly useful. 606 $aSocial sciences$xStatistical methods 606 $aStatistics 606 $aPsychometrics 606 $aStatistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy 606 $aStatistical Theory and Methods 606 $aPsychometrics 615 0$aSocial sciences$xStatistical methods. 615 0$aStatistics. 615 0$aPsychometrics. 615 14$aStatistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy. 615 24$aStatistical Theory and Methods. 615 24$aPsychometrics. 676 $a300.721 700 $aStemmler$b Mark$0721626 701 $aWiedermann$b Wolfgang$01732770 701 $aHuang$b Francis L$0283073 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910897991003321 996 $aDependent Data in Social Sciences Research$94211956 997 $aUNINA