Forms, Issues, and Methods of Analysis Stemmler, Mark. editor. edt http://id.loc.gov/vocabulary/relators/edt Wiedermann, Wolfgang. editor. edt http://id.loc.gov/vocabulary/relators/edt Huang, Francis L. editor. edt http://id.loc.gov/vocabulary/relators/edt SpringerLink (Online service) text sz 2024 2nd ed. 2024. monographic eng

electronic

electronic resource

access XXII, 786 p. 70 illus., 64 illus. in color. online resource. This 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. Growth Curve Modeling -- Directional Dependence -- Dydatic Data Modeling -- Item Response Modeling -- Other Methods for the Analyses of Dependent Data. edited by Mark Stemmler, Wolfgang Wiedermann, Francis L. Huang. Social sciences Statistical methods Statistics Psychometrics Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy Statistical Theory and Methods Psychometrics HA1-4737 9783031563188 https://doi.org/10.1007/978-3-031-56318-8 https://doi.org/10.1007/978-3-031-56318-8 241021 20251030113237.0 978-3-031-56318-8