Applied Logistic Regression

ISBN-10: 0471356328
ISBN-13: 9780471356325
Edition: 2nd 2000 (Revised)
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Description: Since the late 1960s the logistic regression (LR) model has become the standard method for regression analysis in many fields. This text offers an introduction to the LR model and examines its use in methods for modelling.

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Book details

List price: $165.00
Edition: 2nd
Copyright year: 2000
Publisher: John Wiley & Sons, Incorporated
Publication date: 9/27/2000
Binding: Hardcover
Pages: 392
Size: 6.25" wide x 9.25" long x 1.00" tall
Weight: 1.628

Since the late 1960s the logistic regression (LR) model has become the standard method for regression analysis in many fields. This text offers an introduction to the LR model and examines its use in methods for modelling.

Introduction to the Logistic Regression Model
Introduction
Fitting the Logistic Regression Model
Testing for the Significance of the Coefficients
Confidence Interval Estimation
Other Methods of Estimation
Data Sets
The ICU Study
The Low Birth Weight Study
The Prostate Cancer Study
The UMARU IMPACT Study
Exercises
Multiple Logistic Regression
Introduction
The Multiple Logistic Regression Model
Fitting the Multiple Logistic Regression Model
Testing for the Significance of the Model
Confidence Interval Estimation
Other Methods of Estimation
Exercises
Interpretation of the Fitted Logistic Regression Model
Introduction
Dichotomous Independent Variable
Polychotomous Independent Variable
Continuous Independent Variable
The Multivariable Model
Interaction and Confounding
Estimation of Odds Ratios in the Presence of Interaction
A Comparison of Logistic Regression and Stratified Analysis for 2 [times] 2 Tables
Interpretation of the Fitted Values
Exercises
Model-Building Strategies and Methods for Logistic Regression
Introduction
Variable Selection
Stepwise Logistic Regression
Best Subsets Logistic Regression
Numerical Problems
Exercises
Assessing the Fit of the Model
Introduction
Summary Measures of Goodness-of-Fit
Pearson Chi-Square Statistic and Deviance
The Hosmer-Lemeshow Tests
Classification Tables
Area Under the ROC Curve
Other Summary Measures
Logistic Regression Diagnostics
Assessment of Fit via External Validation
Interpretation and Presentation of Results from a Fitted Logistic Regression Model
Exercises
Application of Logistic Regression with Different Sampling Models
Introduction
Cohort Studies
Case-Control Studies
Fitting Logistic Regression Models to Data from Complex Sample Surveys
Exercises
Logistic Regression for Matched Case-Control Studies
Introduction
Logistic Regression Analysis for the 1-1 Matched Study
An Example of the Use of the Logistic Regression Model in a 1-1 Matched Study
Assessment of Fit in a Matched Study
An Example of the Use of the Logistic Regression Model in a 1-M Matched Study
Methods for Assessment of Fit in a 1-M Matched Study
An Example of Assessment of Fit in a 1-M Matched Study
Exercises
Special Topics
The Multinomial Logistic Regression Model
Introduction to the Model and Estimation of the Parameters
Interpreting and Assessing the Significance of the Estimated Coefficients
Model-Building Strategies for Multinomial Logistic Regression
Assessment of Fit and Diagnostics for the Multinomial Logistic Regression Model
Ordinal Logistic Regression Models
Introduction to the Models, Methods for Fitting and Interpretation of Model Parameters
Model Building Strategies for Ordinal Logistic Regression Models
Logistic Regression Models for the Analysis of Correlated Data
Exact Methods for Logistic Regression Models
Sample Size Issues When Fitting Logistic Regression Models
Exercises
References
Index

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