000 01838nam a2200229Ia 4500
008 140323b2007 xxu||||| |||| 00| 0 eng d
020 _a9780521686891
082 _a519.536
100 _aGelman, Andrew
245 _aData analysis using regression and multilevel/hierarchical models
_cGelman, Andrew
260 _aCambridge
_bCambridge University Press
300 _axxii, 625 p.
365 _bUSD 21.99
440 _aAnalytical methods for social research
520 _aData 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, post stratification, 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.
650 _aRegression analysis
650 _aMultilevel models (Statistics)
700 _aHill, Jennifer
942 _cBK
952 _w2009-09-04
_DHimanshu Book Co.,
_MProf. Venkata Rao V
_o519.536 G3D2
999 _c63151