Dependent Data in Social Sciences Research: Forms, Issues, and Methods of Analysis

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Mark Stemmler Wolfgang Wiedermann

Dependent Data in Social Sciences Research

Forms, Issues, and Methods of Analysis

Mark Stemmler, Wolfgang Wiedermann, Francis L. Huang

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English

Springer International Publishing AG
22 October 2024

Social research & statistics; Psychological testing & measurement; Probability & statistics

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.

Edited by: Mark Stemmler, Wolfgang Wiedermann, Francis L. Huang
Imprint: Springer International Publishing AG
Country of Publication: Switzerland
Edition: Second Edition 2024
Dimensions: Height: 235mm, Width: 155mm,
ISBN: 9783031563171
ISBN 10: 3031563174
Pages: 786
Publication Date: 22 October 2024
Audience: Professional and scholarly , Undergraduate
Format: Hardback
Publisher's Status: Active

Growth Curve Modeling.- Directional Dependence.- Dydatic Data Modeling.- Item Response Modeling.- Other Methods for the Analyses of Dependent Data.

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).