Fixed Effects Regression Models
Paul D. Allison
- University of Pennsylvania
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Go to College Publishing WebsiteDescription
This book demonstrates how to estimate and interpret fixed-effects models in a variety of different modeling contexts: linear models, logistic models, Poisson models, Cox regression models, and structural equation models. Both advantages and disadvantages of fixed-effects models will be considered, along with detailed comparisons with random-effects models. Written at a level appropriate for anyone who has taken a year of statistics, the book is appropriate as a supplement for graduate courses in regression or linear regression as well as an aid to researchers who have repeated measures or cross-sectional data.
Learn more about "The Little Green Book" - QASS Series! Click Here
Contents
About the Author
About the Author
Series Editor's Introduction
Series Editor's Introduction
1. Introduction
1. Introduction
2. Linear Fixed Effects Models: Basics
2. Linear Fixed Effects Models: Basics
3. Fixed Effects Logistic Models
3. Fixed Effects Logistic Models
4. Fixed Effects Models for Count Data
4. Fixed Effects Models for Count Data
5. Fixed Effects Models for Events History Data
5. Fixed Effects Models for Events History Data
6. Structural Equation Models With Fixed Effects
6. Structural Equation Models With Fixed Effects
Appendix 1
Appendix 1
Appendix 2
Appendix 2
References
References
Author Index
Author Index
Subject Index
Subject Index
Description
This book demonstrates how to estimate and interpret fixed-effects models in a variety of different modeling contexts: linear models, logistic models, Poisson models, Cox regression models, and structural equation models. Both advantages and disadvantages of fixed-effects models will be considered, along with detailed comparisons with random-effects models. Written at a level appropriate for anyone who has taken a year of statistics, the book is appropriate as a supplement for graduate courses in regression or linear regression as well as an aid to researchers who have repeated measures or cross-sectional data.
Learn more about "The Little Green Book" - QASS Series! Click Here
Contents
About the Author
About the Author
Series Editor's Introduction
Series Editor's Introduction
1. Introduction
1. Introduction
2. Linear Fixed Effects Models: Basics
2. Linear Fixed Effects Models: Basics
3. Fixed Effects Logistic Models
3. Fixed Effects Logistic Models
4. Fixed Effects Models for Count Data
4. Fixed Effects Models for Count Data
5. Fixed Effects Models for Events History Data
5. Fixed Effects Models for Events History Data
6. Structural Equation Models With Fixed Effects
6. Structural Equation Models With Fixed Effects
Appendix 1
Appendix 1
Appendix 2
Appendix 2
References
References
Author Index
Author Index
Subject Index
Subject Index
April 2009 | 136 pages | Sage US
| Format | Published Date | ISBN | Price |
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This book demonstrates how to estimate and interpret fixed-effects models in a variety of different modeling contexts: linear models, logistic models, Poisson models, Cox regression models, and structural equation models. Both advantages and disadvantages of fixed-effects models will be considered, along with detailed comparisons with random-effects models. Written at a level appropriate for anyone who has taken a year of statistics, the book is appropriate as a supplement for graduate courses in regression or linear regression as well as an aid to researchers who have repeated measures or cross-sectional data.
Learn more about "The Little Green Book" - QASS Series! Click Here
Table Of Contents:
- About the Author
- Series Editor's Introduction
- 1. Introduction
- 2. Linear Fixed Effects Models: Basics
- 3. Fixed Effects Logistic Models
- 4. Fixed Effects Models for Count Data
- 5. Fixed Effects Models for Events History Data
- 6. Structural Equation Models With Fixed Effects
- Appendix 1
- Appendix 2
- References
- Author Index
- Subject Index