Regression Models as a Tool in Medical Research
""With its focus on conceptual understanding and practical applications, this book is highly recommended to medical and other health science researchers who desire to improve their understanding of regression analysis for a better understanding of medical literature, for the adequate prese...
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| Format: | Book |
| Language: | English |
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Hoboken :
CRC Press,
2012
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Table of Contents:
- Front Cover; Dedication; Contents; Preface; Acknowledgments; About the Author; Part I The Basics; Chapter 1 Why Use Regression Models?; Chapter 2 An Introductory Example; Chapter 3 The Classical Multiple Regression Model; Chapter 4 Adjusted Effects; Chapter 5 Inference for the Classical Multiple Regression Model; Chapter 6 Logistic Regression; Chapter 7 Inference for the Logistic Regression Model; Chapter 8 Categorical Covariates; Chapter 9 Handling Ordered Categories: A First Lesson in Regression Modelling Strategies; Chapter 10 The Cox Proportional Hazards Model
- Appendix A Mathematics Behind the Classical Linear Regression ModelAppendix B Mathematics Behind the Logistic Regression Model; Appendix C The Modern Way of Inference; Appendix D Mathematics for Risk Scores and Predictors; Bibliography; Back Cover
- Chapter 11 Common Pitfalls in Using Regression ModelsPart II Advanced Topics and Techniques; Chapter 12 Some Useful Technicalities; Chapter 13 Comparing Regression Coefficients; Chapter 14 Power and Sample Size; Chapter 15 Selection of the Sample; Chapter 16 Selection of Covariates; Chapter 17 Modelling Nonlinear Effects; Chapter 18 Transformation of Covariates; Chapter 19 Effect Modification and Interactions; Chapter 20 Applying Regression Models to Clustered Data; Chapter 21 Applying Regression Models to Longitudinal Data; Chapter 22 The Impact of Measurement Error
- Chapter 23 The Impact of Incomplete Covariate DataPart III Risk Scores and Predictors; Chapter 24 Risk Scores; Chapter 25 Construction of Predictors; Chapter 26 Evaluating the Predictive Performance; Chapter 27 Outlook: Construction of Parsimonious Predictors; Part IV Miscellaneous; Chapter 28 Alternatives to Regression Modelling; Chapter 29 Specific Regression Models; Chapter 30 Specific Usages of Regression Models; Chapter 31 What Is a Good Model?; Chapter 32 Final Remarks on the Role of Prespecified Models and Model Development; Part V Mathematical Details