Logistic regression: a self-learning text

Logistic regression: a self-learning text

Kleinbaum, David G.
Klein, Mitchel

93,55 €(IVA inc.)

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 inthe main text. INDICE: Introduction to logistic regression.- Important special cases of the logistic model.- Computing the odds ratio in logistic regression.- Maximum likelihood techniques: An overview.- Statistical inferences using maximum likelihood techniques.- modeling strategy guidelines.- Modeling strategy for assessing interaction and confounding.- Additional modeling strategy issues.- Assessing Goodness of Fit for logistic regression.- Assessing discriminatory performance of a binary logistic regression model: ROC curves.- Analysis of matched data using logistic regression.- Polytomous logistic regression.- Ordinal logistic regression.- Logistic regression for correlated data: GEE.- GEE examples.- Other approaches for analysis of correlated data.

  • ISBN: 978-1-4419-1741-6
  • Editorial: Springer
  • Encuadernacion: Cartoné
  • Páginas: 616
  • Fecha Publicación: 01/06/2010
  • Nº Volúmenes: 1
  • Idioma: Inglés