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Data Analysis Using Regression and Multilevel/Hierarchical Models
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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.
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Cambridge University Press; December 2006
ISBN 9781139234962
Read online, or download in EPUB or secure PDF format
ISBN 9781139234962
Read online, or download in EPUB or secure PDF format
Subject categories
- Academic > Statistics > Theory and method of social science statistics > Statistics; Graphic methods
- Academic > Statistics > Theory and method of social science statistics > Regression analysis
- Mathematics > Probability & Statistics
- Psychology & Psychiatry > Assessment, Testing & Measurement
- Social Science > Sociology
ISBNs
0511266839
9780511266836
9780521867061
9781139234962

