Home Page Icon
Home Page
Table of Contents for
Cover
Close
Cover
by Rodney X. Sturdivant, Stanley Lemeshow, David W. Hosmer, Jr.
Applied Logistic Regression, 3rd Edition
Cover
Series
Title Page
Copyright
Dedication
Preface to the Third Edition
Chapter 1: 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 Estimation Methods
1.6 Data Sets Used in Examples and Exercises
Exercises
Chapter 2: The Multiple Logistic Regression Model
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 Estimation Methods
Exercises
Chapter 3: Interpretation of the Fitted Logistic Regression Model
3.1 Introduction
3.2 Dichotomous Independent Variable
3.3 Polychotomous Independent Variable
3.4 Continuous Independent Variable
3.5 Multivariable Models
3.6 Presentation and Interpretation of the Fitted Values
3.7 A Comparison of Logistic Regression and Stratified Analysis for 2 × 2 Tables
Exercises
Chapter 4: Model-Building Strategies and Methods for Logistic Regression
4.1 Introduction
4.2 Purposeful Selection of Covariates
4.3 Other Methods for Selecting Covariates
4.4 Numerical Problems
Exercises
Chapter 5: Assessing the Fit of the Model
5.1 Introduction
5.2 Summary Measures of Goodness of Fit
5.3 Logistic Regression Diagnostics
5.4 Assessment of Fit Via External Validation
5.5 Interpretation and Presentation of the Results from a Fitted Logistic Regression Model
Exercises
Chapter 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
Chapter 7: Logistic Regression for Matched Case-Control Studies
7.1 Introduction
7.2 Methods For Assessment of Fit in a 1− M Matched Study
7.3 An Example Using the Logistic Regression Model in a Matched Study
7.4 An Example Using the Logistic Regression Model in a Matched Study
Exercises
Chapter 8: Logistic Regression Models for Multinomial and Ordinal Outcomes
8.1 The Multinomial Logistic Regression Model
8.2 Ordinal Logistic Regression Models
Exercises
Chapter 9: Logistic Regression Models for the Analysis of Correlated Data
9.1 Introduction
9.2 Logistic Regression Models for the Analysis of Correlated Data
9.3 Estimation Methods for Correlated Data Logistic Regression Models
9.4 Interpretation of Coefficients From Logistic Regression Models for the Analysis of Correlated Data
9.5 An Example of Logistic Regression Modeling with Correlated Data
9.6 Assessment of Model Fit
Exercises
Chapter 10: Special Topics
10.1 Introduction
10.2 Application of Propensity Score Methods in Logistic Regression Modeling
10.3 Exact Methods for Logistic Regression Models
10.4 Missing Data
10.5 Sample Size Issues When Fitting Logistic Regression Models
10.6 Bayesian Methods for Logistic Regression
10.7 Other Link Functions for Binary Regression Models
10.8 Mediation ‡
10.9 More About Statistical Interaction
Exercises
References
Index
Search in book...
Toggle Font Controls
Playlists
Add To
Create new playlist
Name your new playlist
Playlist description (optional)
Cancel
Create playlist
Sign In
Email address
Password
Forgot Password?
Create account
Login
or
Continue with Facebook
Continue with Google
Sign Up
Full Name
Email address
Confirm Email Address
Password
Login
Create account
or
Continue with Facebook
Continue with Google
Next
Next Chapter
Table of Contents
Add Highlight
No Comment
..................Content has been hidden....................
You can't read the all page of ebook, please click
here
login for view all page.
Day Mode
Cloud Mode
Night Mode
Reset