500分悬赏” Regression Models as a Tool in Medical Research”

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http://www.stata.com/bookstore/regression-models-as-a-tool-in-medical-research/

Regression Models as a Tool in Medical Research (2013)

Regression Models as a Tool in Medical Research, by Werner Vach, is a practical guide to regression analysis for medical researchers. It describes the important aspects of regression models for continuous, binary, survival, and count outcomes—all commonly encountered in medical research. The regression models covered include linear regression, logistic regression, Cox regression, and Poisson regression. The book also discusses methods to handle different types of data structures such as matched case–control data and longitudinal data. The “hands-on” examples reinforce the concepts described in each chapter, and the “in-a-nutshell” summaries after each chapter provide a quick refresher of the topics covered.

The book has five parts. The first part covers the basic concepts of the linear, logistic, and Cox regressions commonly used to analyze medical data. The second part discusses more advanced topics such as modeling of nonlinear effects and analysis of longitudinal and clustered data, as well as sample-size and power considerations when designing a study. The third part concentrates on prediction, and the fourth part briefly covers some alternatives to regression modeling. Finally, the fifth part provides mathematical details behind the main regression concepts.

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关键词：regression regressio Research Medical regress continuous describes important practical research

Table of contents :
Content: 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 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 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

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楼主,这本书500有点贵了,虽然我悬赏500分,
但是你上传的这本书有问题呢
书中大量乱码
能否麻烦你在上传一个无乱码的版本.

这本电子书以前我没有看过，刚才看了看确实里面有很多乱码。请版主退回论坛币吧