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Applied Logistic Regression, 2nd Edition
Comment from the Stata technical groupThe second edition of Applied Logistic Regression, by David W. Hosmer and Stanley Lemeshow, provides an excellent updated reference to the advances in methodology in logistic regression that have taken place over the last 10 years. While the first edition has served as one of the few comprehensive treatments of logistic regression available, the second edition introduces many enhancements in the areas of assessing model fit, estimation using data from complex survey samples, regression models for multinomial data, ordinal data, and data with correlated responses. Also, the text now covers exact tests and sample size calculations. Many of the analyses in the book were performed in Stata and can be replicated in Stata with data from the text. In particular, Stata’s svy: logit command can be used to fit logistic regression models with survey data. To download the data in Stata format, click here. Table of contents1. Introduction to the Logistic Regression Model
1.1 Introduction
1.2 Fitting the Logistic Regression Model 1.3 Testing for the Significance of the Coefficients 1.4 Confidence Interval Estimation 1.5 Other Methods of Estimation 1.6 Data Sets
1.6.1 The ICU Study
Exercises
1.6.2 The Low Birth Weight Study 1.6.3 The Prostate Cancer Study 1.6.4 The UMARU IMPACT Study 2. Multiple Logistic Regression
2.1 Introduction
2.2 The Multiple Logistic Regression Model 2.3 Fitting the Multiple Logistic Regression Model 2.4 Testing for the Significance of the Model 2.5 Confidence Interval Estimation 2.6 Other Methods of Estimation Exercises 3. Interpretation of the Fitted Logistic Regression Model
3.1 Introduction
3.2 Dichotomous Independent Variable 3.3 Polytomous Independent Variable 3.4 Continuous Independent Variable 3.5 The Multivariate Model 3.6 Interaction and Confounding 3.7 Estimation of Odds Ratios in the Presence of Interaction 3.8 A Comparison of Logistic Regression and Stratified Analysis for 2×2 Tables Exercises 4. Model-Building Strategies and Methods for Logistic Regression
4.1 Introduction
4.2 Variable Selection 4.3 Stepwise Logistic Regression 4.4 Best Subsets Logistic Regression 4.5 Numerical Problems Exercises 5. Assessing the Fit of the Model
5.1 Introduction
5.2 Summary Measures of Goodness-of-Fit
5.2.1 Pearson Chi-Square Statistic and Deviance
5.3 Logistic Regression Diagnostics 5.2.2 The Hosmer–Lemeshow Tests 5.2.3 Classification Tables 5.2.4 Area Under the ROC Curve 5.2.5 Other Summary Measures 5.4 Assessment of Fit via External Validation 5.5 Interpretation and Presentation of Results from a Fitted Logistic Regression Model Exercises 6. Application of Logistic Regression with Different Sampling Models
6.1 Introduction
6.2 Cohort Studies 6.3 Case-Control Studies 6.4 Fitting Logistic Regression Models to Data from Complex Sample Surveys Exercises 7. Logistic Regression for Matched Case-Control Studies
7.1 Introduction
7.2 Logistic Regression Analysis for the 1-1 Matched Study 7.3 An Example of the Use of the Logistic Regression Model in a 1-1 Matched Study 7.4 Assessment of Fit in a 1-1 Matched Study 7.5 An Example of the Use of the Logistic Regression Model in a 1-M Matched Study 7.6 Methods for Assessment of Fit in a 1-M Matched Study 7.7 An Example of Assessment of Fit in a 1-M Matched Study Exercises 8. Special Topics
8.1 The Multinomial Logistic Regression Model
8.1.1 Introduction to the Model and Estimation of the Parameters
8.2 Ordinal Logistic Regression Models
8.1.2 Interpreting and Assessing the Significance of the Estimated Coefficients 8.1.3 Model-Building Strategies for Multinomial Logistic Regression 8.1.4 Assessment of Fit and Diagnostics for the Multinomial Logistic Regression Model
8.2.1 Introduction to the Models, Methods for Fitting and Interpretation of Model Parameters
8.3 Logistic Regression Models for the Analysis of Correlated Data 8.2.2 Model Building Models for the Analysis of Correlated Data 8.4 Exact Methods for Logistic Regression Models 8.5 Sample Size Issues When Fitting Logistic Regression Models Exercises References
Index
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