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Logistic Regression: A Self-learning Text

Logistic Regression: A Self-learning Text

David G. Kleinbaum, Mitchel Klein
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This very popular textbook is now in its third edition. Whether students or working professionals, readers appreciate its unique "lecture book" format. They often say the book reads like they are listening to an outstanding lecturer. This edition includes three new chapters, an updated computer appendix, and an expanded section about modeling guidelines that consider causal diagrams. Like previous editions, this textbook provides a highly readable description of fundamental and more advanced concepts and methods of logistic regression. It is suitable for researchers and statisticians in medical and other life sciences as well as academicians teaching second-level regression methods courses. The new chapters are: Additional Modeling Strategy Issues, including strategy with several exposures, screening variables, collinearity, influential observations and multiple-testing, assessing Goodness to Fit for Logistic Regression, assessing Discriminatory Performance of a Binary Logistic Model: ROC Curves. The Computer Appendix provides step-by-step instructions for using STATA (version 10.0), SAS (version 9.2), and SPSS (version 16) for procedures described in the main text.
Année:
2002
Edition:
3rd ed.
Editeur::
Springer
Langue:
english
Pages:
528
ISBN 10:
1441917411
ISBN 13:
9781441917416
Collection:
Statistics for Biology and Health
Fichier:
PDF, 1.95 MB
IPFS:
CID , CID Blake2b
english, 2002
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