Biostatistics and Computer-Based Analysis of Health Data Using the R Software addresses the concept that many of the actions performed by statistical software comes back to the handling, manipulation, or even transformation of digital data.
It is therefore of primary importance to understand how statistical data is displayed and how it can be exploited by software such as R. In this book, the authors explore basic and variable commands, sample comparisons, analysis of variance, epidemiological studies, and censored data.
With proposed applications and examples of commands following each chapter, this book allows readers to apply advanced statistical concepts to their own data and software.
1. Introduction - p. ix 2. 1: Elements of the Language - p. 1 3. 2: Descriptive Statistics and Estimation - p. 23 4. 3: Measures and Tests of Association Between Two Variables - p. 41 5. 4: Analysis of Variance and Experimental Design - p. 65 6. 5: Correlation and Linear Regression - p. 89 7. 6: Measures of Association in Epidemiology and Logistic Regression - p. 111 8. 7: Survival Data Analysis - p. 137 9. Appendix 1: Introduction to RStudio - p. 157 10. Appendix 2: Graphs with the Lattice Package - p. 161 11. Appendix 3: The Hmisc and rms Packages - p. 173 12. Bibliography - p. 187 13. Index - p. 191
Biostatistics and Computer-Based Analysis of Health Data Using the R Software addresses the concept that many of the actions performed by statistical software comes back to the handling, manipulation, or even transformation of digital data.
It is therefore of primary importance to understand how statistical data is displayed and how it can be exploited by software such as R. In this book, the authors explore basic and variable commands, sample comparisons, analysis of variance, epidemiological studies, and censored data.
With proposed applications and examples of commands following each chapter, this book allows readers to apply advanced statistical concepts to their own data and software.
1. Introduction - p. ix 2. 1: Elements of the Language - p. 1 3. 2: Descriptive Statistics and Estimation - p. 23 4. 3: Measures and Tests of Association Between Two Variables - p. 41 5. 4: Analysis of Variance and Experimental Design - p. 65 6. 5: Correlation and Linear Regression - p. 89 7. 6: Measures of Association in Epidemiology and Logistic Regression - p. 111 8. 7: Survival Data Analysis - p. 137 9. Appendix 1: Introduction to RStudio - p. 157 10. Appendix 2: Graphs with the Lattice Package - p. 161 11. Appendix 3: The Hmisc and rms Packages - p. 173 12. Bibliography - p. 187 13. Index - p. 191
