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Dependent data in social sciences research[electronic resource] :forms, issues, and methods of analysis /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	300.72
書名/作者:	Dependent data in social sciences research : forms, issues, and methods of analysis // edited by Mark Stemmler, Alexander von Eye, Wolfgang Wiedermann.
其他作者:	Stemmler, Mark.
出版者:	Cham : : Springer International Publishing :, 2015.
面頁冊數:	xiii, 385 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Social sciences - Research
標題:	Social sciences - Statistical methods.
標題:	Statistics.
標題:	Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law.
標題:	Statistical Theory and Methods.
標題:	Psychometrics.
ISBN:	9783319205854
ISBN:	9783319205847
內容註:	Growth Curve Modeling -- Directional Dependence -- Dydatic Data Modeling -- Item Response Modeling -- Other Methods for the Analyses of Dependent Data.
摘要、提要註:	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.
電子資源:	http://dx.doi.org/10.1007/978-3-319-20585-4

Dependent data in social sciences research[electronic resource] :forms, issues, and methods of analysis /
Dependent data in social sciences researchforms, issues, and methods of analysis /[electronic resource] :edited by Mark Stemmler, Alexander von Eye, Wolfgang Wiedermann. - Cham :Springer International Publishing :2015. - xiii, 385 p. :ill., digital ;24 cm. - Springer proceedings in mathematics & statistics,v.1452194-1009 ;. - Springer proceedings in mathematics & statistics ;v.70..

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

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.

ISBN: 9783319205854

Standard No.: 10.1007/978-3-319-20585-4doiSubjects--Topical Terms:

336674
Social sciences
--Research

LC Class. No.: H62.A5

Dewey Class. No.: 300.72

Dependent data in social sciences research[electronic resource] :forms, issues, and methods of analysis /
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