Logistic Regression
A Self-Learning Text
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ISBN-13:
9781441917416
Veröffentl:
2010
Erscheinungsdatum:
01.07.2010
Seiten:
702
Autor:
David G Kleinbaum
Gewicht:
1472 g
Format:
265x189x46 mm
Sprache:
Englisch
Beschreibung:
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.
Includes supplementary material: sn.pub/extras
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 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.
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