Dependent data in social sciences research: forms, issues, and methods of analysis
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 mod...
Gespeichert in:
| Weitere beteiligte Personen: | , , |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Cham, Switzerland
Springer
[2024]
|
| Ausgabe: | Second edition |
| Schlagwörter: | |
| Zusammenfassung: | 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 |
| Umfang: | xxii, 786 Seiten Illustrationen, Diagramme |
| ISBN: | 9783031563171 9783031563201 |
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| 520 | |a 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 | ||
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| id | DE-604.BV050042815 |
| illustrated | Illustrated |
| indexdate | 2025-02-10T11:05:51Z |
| institution | BVB |
| isbn | 9783031563171 9783031563201 |
| language | English |
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| physical | xxii, 786 Seiten Illustrationen, Diagramme |
| publishDate | 2024 |
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| publisher | Springer |
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| spelling | Dependent data in social sciences research forms, issues, and methods of analysis Mark Stemmler, Wolfgang Wiedermann, Francis L. Huang, editors Second edition Cham, Switzerland Springer [2024] xxii, 786 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier 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 Statistics Psychometrics Social sciences—Statistical methods Wechselwirkung (DE-588)4064937-4 gnd rswk-swf Statistik (DE-588)4056995-0 gnd rswk-swf Hardcover, Softcover / Soziologie/Methoden der empirischen und qualitativen Sozialforschung Wechselwirkung (DE-588)4064937-4 s Statistik (DE-588)4056995-0 s DE-604 Stemmler, Mark 1960- (DE-588)135954789 edt Wiedermann, Wolfgang 1981- (DE-588)1108324592 edt Huang, Francis (DE-588)1302375253 edt Erscheint auch als Online-Ausgabe 978-3-031-56318-8 |
| spellingShingle | Dependent data in social sciences research forms, issues, and methods of analysis Statistics Psychometrics Social sciences—Statistical methods Wechselwirkung (DE-588)4064937-4 gnd Statistik (DE-588)4056995-0 gnd |
| subject_GND | (DE-588)4064937-4 (DE-588)4056995-0 |
| title | Dependent data in social sciences research forms, issues, and methods of analysis |
| title_auth | Dependent data in social sciences research forms, issues, and methods of analysis |
| title_exact_search | Dependent data in social sciences research forms, issues, and methods of analysis |
| title_full | Dependent data in social sciences research forms, issues, and methods of analysis Mark Stemmler, Wolfgang Wiedermann, Francis L. Huang, editors |
| title_fullStr | Dependent data in social sciences research forms, issues, and methods of analysis Mark Stemmler, Wolfgang Wiedermann, Francis L. Huang, editors |
| title_full_unstemmed | Dependent data in social sciences research forms, issues, and methods of analysis Mark Stemmler, Wolfgang Wiedermann, Francis L. Huang, editors |
| title_short | Dependent data in social sciences research |
| title_sort | dependent data in social sciences research forms issues and methods of analysis |
| title_sub | forms, issues, and methods of analysis |
| topic | Statistics Psychometrics Social sciences—Statistical methods Wechselwirkung (DE-588)4064937-4 gnd Statistik (DE-588)4056995-0 gnd |
| topic_facet | Statistics Psychometrics Social sciences—Statistical methods Wechselwirkung Statistik |
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