Data analysis using regression and multilevel/hierarchical models

"Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructi...

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Bibliographische Detailangaben
1. Verfasser: Gelman, Andrew (VerfasserIn)
Weitere Verfasser: Hill, Jennifer (VerfasserIn)
Format: UnknownFormat
Sprache:eng
Veröffentlicht: Cambridge u.a. Cambridge University Press 2007
Ausgabe:1. publ.
Schriftenreihe:Analytical methods for social research
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Beschreibung
Zusammenfassung:"Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout."--Publisher description
Beschreibung:Hier auch später erschienene, unveränderte Nachdrucke
Includes bibliographical references
Beschreibung:XXII, 625 S.
Ill., graph. Darst.
26 cm
ISBN:0521867061
0-521-86706-1
052168689X
0-521-68689-X
9780521867061
978-0-521-86706-1
9780521686891
978-0-521-68689-1