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Více informací o knize Dependent Data in Social Sciences Research

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Anotace knihy

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.

Parametry knihy

Zařazení knihy Knihy v angličtině Society & social sciences Sociology & anthropology Sociology

• Plný název: Dependent Data in Social Sciences Research
• Podnázev: Forms, Issues, and Methods of Analysis
• Autor: Mark Stemmler, Wolfgang Wiedermann, Francis L. Huang
• Jazyk: Angličtina
• Vazba: Pevná
• Počet stran: 808
• EAN: 9783031563171
• ID: 44806427
• Nakladatelství: Springer, Berlin
• Hmotnost: 1304 g
• Rozměry: 235 × 155 mm
• Datum vydání: 21. July 2024

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