Dependent Data in Social Sciences Research
Springer International Publishing (Verlag)
978-3-031-56317-1 (ISBN)
This book covers the following subjects: growth curve modeling, directional dependence, dyadic data modeling, item response modeling (IRT), and other methods for the analysis of dependent data (e.g., approaches for modeling cross-section dependence, multidimensional scaling techniques, and mixed models). 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. These include, for example, methods for the analysis of longitudinal data, corrections for dependency, and corrections for degrees of freedom.
Researchers and graduate students in the social and behavioral sciences, education, econometrics, and medicine will find this up-to-date overview of modern statistical approaches for dealing with problems related to dependent data particularly useful.
Mark Stemmler is Professor at Friedrich Alexander University Erlangen-Nuremberg (FAU), Department of Psychology
Wolfgang Wiedermann is Associate Professor, College of Education and Human Development, Co-Director of the Methodology Branch of the Missouri Prevention Science Institute, University of Missouri-Columbia (US).
Francis L. Huang is Associate Professor, College of Education and Human Development, Co-Director of the Methodology Branch of the Missouri Prevention Science Institute, University of Missouri-Columbia (US).
Growth Curve Modeling.- Directional Dependence.- Dydatic Data Modeling.- Item Response Modeling.- Other Methods for the Analyses of Dependent Data.
| Erscheinungsdatum | 23.10.2024 |
|---|---|
| Zusatzinfo | XXII, 786 p. 70 illus., 64 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Geisteswissenschaften ► Psychologie ► Test in der Psychologie |
| Mathematik / Informatik ► Mathematik | |
| Sozialwissenschaften ► Soziologie ► Empirische Sozialforschung | |
| Schlagworte | Analysis of longitudinal panel count data • close proximity data • clustered or paired data • corrections for dependency • dependent data • directional dependence • dyadic data modeling • growth curve modeling • item response modeling • Psychometrics • statistical analysis for dependence in data |
| ISBN-10 | 3-031-56317-4 / 3031563174 |
| ISBN-13 | 978-3-031-56317-1 / 9783031563171 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
aus dem Bereich
