Applied Logistic Regression, 3rd Edition

Table of contents

1. Cover
2. Series
3. Title Page
4. Copyright
5. Dedication
6. Preface to the Third Edition
7. Chapter 1: Introduction to the Logistic Regression Model
   1. 1.1 Introduction
   2. 1.2 Fitting the Logistic Regression Model
   3. 1.3 Testing for the Significance of the Coefficients
   4. 1.4 Confidence Interval Estimation
   5. 1.5 Other Estimation Methods
   6. 1.6 Data Sets Used in Examples and Exercises
   7. Exercises
8. Chapter 2: The Multiple Logistic Regression Model
   1. 2.1 Introduction
   2. 2.2 The Multiple Logistic Regression Model
   3. 2.3 Fitting the Multiple Logistic Regression Model
   4. 2.4 Testing for the Significance of the Model
   5. 2.5 Confidence Interval Estimation
   6. 2.6 Other Estimation Methods
   7. Exercises
9. Chapter 3: Interpretation of the Fitted Logistic Regression Model
   1. 3.1 Introduction
   2. 3.2 Dichotomous Independent Variable
   3. 3.3 Polychotomous Independent Variable
   4. 3.4 Continuous Independent Variable
   5. 3.5 Multivariable Models
   6. 3.6 Presentation and Interpretation of the Fitted Values
   7. 3.7 A Comparison of Logistic Regression and Stratified Analysis for 2 × 2 Tables
   8. Exercises
10. Chapter 4: Model-Building Strategies and Methods for Logistic Regression
    1. 4.1 Introduction
    2. 4.2 Purposeful Selection of Covariates
    3. 4.3 Other Methods for Selecting Covariates
    4. 4.4 Numerical Problems
    5. Exercises
11. Chapter 5: Assessing the Fit of the Model
    1. 5.1 Introduction
    2. 5.2 Summary Measures of Goodness of Fit
    3. 5.3 Logistic Regression Diagnostics
    4. 5.4 Assessment of Fit Via External Validation
    5. 5.5 Interpretation and Presentation of the Results from a Fitted Logistic Regression Model
    6. Exercises
12. Chapter 6: Application of Logistic Regression with Different Sampling Models
    1. 6.1 Introduction
    2. 6.2 Cohort Studies
    3. 6.3 Case-Control Studies
    4. 6.4 Fitting Logistic Regression Models to Data From Complex Sample Surveys
    5. Exercises
13. Chapter 7: Logistic Regression for Matched Case-Control Studies
    1. 7.1 Introduction
    2. 7.2 Methods For Assessment of Fit in a 1− M Matched Study
    3. 7.3 An Example Using the Logistic Regression Model in a Matched Study
    4. 7.4 An Example Using the Logistic Regression Model in a Matched Study
    5. Exercises
14. Chapter 8: Logistic Regression Models for Multinomial and Ordinal Outcomes
    1. 8.1 The Multinomial Logistic Regression Model
    2. 8.2 Ordinal Logistic Regression Models
    3. Exercises
15. Chapter 9: Logistic Regression Models for the Analysis of Correlated Data
    1. 9.1 Introduction
    2. 9.2 Logistic Regression Models for the Analysis of Correlated Data
    3. 9.3 Estimation Methods for Correlated Data Logistic Regression Models
    4. 9.4 Interpretation of Coefficients From Logistic Regression Models for the Analysis of Correlated Data
    5. 9.5 An Example of Logistic Regression Modeling with Correlated Data
    6. 9.6 Assessment of Model Fit
    7. Exercises
16. Chapter 10: Special Topics
    1. 10.1 Introduction
    2. 10.2 Application of Propensity Score Methods in Logistic Regression Modeling
    3. 10.3 Exact Methods for Logistic Regression Models
    4. 10.4 Missing Data
    5. 10.5 Sample Size Issues When Fitting Logistic Regression Models
    6. 10.6 Bayesian Methods for Logistic Regression
    7. 10.7 Other Link Functions for Binary Regression Models
    8. 10.8 Mediation ‡
    9. 10.9 More About Statistical Interaction
    10. Exercises
17. References
18. Index