Book contents
- Frontmatter
- Contents
- Preface
- Acknowledgments
- 1 Introduction
- 2 Principles of Statistics
- 3 Introduction to Linear Regression
- 4 Assessing the Regression
- 5 Multiple Linear Regression
- 6 Indicators, Interactions, and Transformations
- 7 Nonparametric Statistics
- 8 Logistic Regression
- 9 Diagnostics for Logistic Regression
- 10 Poisson Regression
- 11 Survival Analysis
- 12 Proportional Hazards Regression
- 13 Review of Methods
- Appendix: Statistical Tables
- References
- Selected Solutions and Hints
- Index
13 - Review of Methods
Published online by Cambridge University Press: 05 June 2012
- Frontmatter
- Contents
- Preface
- Acknowledgments
- 1 Introduction
- 2 Principles of Statistics
- 3 Introduction to Linear Regression
- 4 Assessing the Regression
- 5 Multiple Linear Regression
- 6 Indicators, Interactions, and Transformations
- 7 Nonparametric Statistics
- 8 Logistic Regression
- 9 Diagnostics for Logistic Regression
- 10 Poisson Regression
- 11 Survival Analysis
- 12 Proportional Hazards Regression
- 13 Review of Methods
- Appendix: Statistical Tables
- References
- Selected Solutions and Hints
- Index
Summary
In the study of statistics, we learn a great many different methods, and it is often unclear which is applicable in a given setting. Half of the problem with data analysis can be traced back to the choice of which method is most appropriate for the data. This chapter provides a review of the methods from the standpoint of the data analyst.
The Appropriate Method
A number of different situations are presented here, and the reader is encouraged to think about the appropriate statistical method for each. In each of the following questions, briefly explain the best statistical technique to solve the problem and specify the null hypothesis.
13.1 I want to estimate how long it takes for seniors to get back to normal living activities following hip surgery. Does it matter whether the surgery is elective or if it follows an accidental fall and fracture? Some people are climbing ladders within four weeks, but others remain in a wheel chair for the rest of their lives. I also want to investigate the effects of other information including age, sex, Medicaid status, and the need for a home health aide. (What methods should we use? What is the null hypothesis?)
[…]
- Type
- Chapter
- Information
- Applied Linear Models with SAS , pp. 247 - 254Publisher: Cambridge University PressPrint publication year: 2010