Overview
- Presents new developments and applications for dependent data
- Applications will be useful for researchers in the social sciences, econometrics, psychometrics, education and medicine
- Features contributions from an international array of researchers
Part of the book series: Springer Proceedings in Mathematics & Statistics (PROMS, volume 145)
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Table of contents (16 papers)
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Front Matter
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Growth Curve Modeling
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Front Matter
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Directional Dependence in Regression Models
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Front Matter
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Item-Response-Modeling
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Front Matter
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Other Methods for the Analyses of Dependent Data
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Front Matter
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Keywords
About this book
This volume 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 methods include, for example, methods for the analysis of longitudinal data, corrections for dependency, and corrections for degrees of freedom. This volume contains the following five sections: 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). 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.
Editors and Affiliations
Bibliographic Information
Book Title: Dependent Data in Social Sciences Research
Book Subtitle: Forms, Issues, and Methods of Analysis
Editors: Mark Stemmler, Alexander von Eye, Wolfgang Wiedermann
Series Title: Springer Proceedings in Mathematics & Statistics
DOI: https://doi.org/10.1007/978-3-319-20585-4
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing Switzerland 2015
Hardcover ISBN: 978-3-319-20584-7Published: 30 October 2015
Softcover ISBN: 978-3-319-37227-3Published: 23 August 2016
eBook ISBN: 978-3-319-20585-4Published: 19 October 2015
Series ISSN: 2194-1009
Series E-ISSN: 2194-1017
Edition Number: 1
Number of Pages: XIII, 385
Topics: Statistics for Social Sciences, Humanities, Law, Statistical Theory and Methods, Psychometrics