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Dependent Data in Social Sciences Research - Forms, Issues, and Methods of Analysis (Paperback, Softcover reprint of the original 1st ed. 2015)
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Dependent Data in Social Sciences Research - Forms, Issues, and Methods of Analysis (Paperback, Softcover reprint of the original 1st ed. 2015)
Series: Springer Proceedings in Mathematics & Statistics, 145
Expected to ship within 10 - 15 working days
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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.
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