This volume of the Biostatistics and Health Sciences Set focuses on statistics applied to clinical research.The use of SAS for data management and statistical modeling is illustrated using various examples. Many aspects of data processing and statistical analysis of cross-sectional and experimental medical data are covered, including regression models commonly found in medical statistics.
This practical book is primarily intended for health researchers with a basic knowledge of statistical methodology. Assuming basic concepts, the authors focus on the practice of biostatistical methods essential to clinical research, epidemiology and analysis of biomedical data (including comparison of two groups, analysis of categorical data, ANOVA, linear and logistic regression, and survival analysis). The use of examples from clinical trials and epidemiological studies provide the basis for a series of practical exercises, which provide instruction and familiarize the reader with essential SAS commands.
1. Introduction - p. ix 2. 1: Language Elements - p. 1 3. 2: Simple Descriptive Statistics - p. 21 4. 3: Measures of Association, Comparison of Means or Proportions - p. 39 5. 4: Correlation, Linear Regression - p. 77 6. 5: Logistic Regression - p. 97 7. 6: Survival Curves, Cox Regression - p. 115 8. Appendix A: Introduction to SAS Studio - p. 143 9. Appendix B: Introduction to SAS Macro - p. 147 10. Appendix C: Introduction to SAS IML - p. 149 11. Bibliography - p. 153 12. Index - p. 155
This volume of the Biostatistics and Health Sciences Set focuses on statistics applied to clinical research.The use of SAS for data management and statistical modeling is illustrated using various examples. Many aspects of data processing and statistical analysis of cross-sectional and experimental medical data are covered, including regression models commonly found in medical statistics.
This practical book is primarily intended for health researchers with a basic knowledge of statistical methodology. Assuming basic concepts, the authors focus on the practice of biostatistical methods essential to clinical research, epidemiology and analysis of biomedical data (including comparison of two groups, analysis of categorical data, ANOVA, linear and logistic regression, and survival analysis). The use of examples from clinical trials and epidemiological studies provide the basis for a series of practical exercises, which provide instruction and familiarize the reader with essential SAS commands.
1. Introduction - p. ix 2. 1: Language Elements - p. 1 3. 2: Simple Descriptive Statistics - p. 21 4. 3: Measures of Association, Comparison of Means or Proportions - p. 39 5. 4: Correlation, Linear Regression - p. 77 6. 5: Logistic Regression - p. 97 7. 6: Survival Curves, Cox Regression - p. 115 8. Appendix A: Introduction to SAS Studio - p. 143 9. Appendix B: Introduction to SAS Macro - p. 147 10. Appendix C: Introduction to SAS IML - p. 149 11. Bibliography - p. 153 12. Index - p. 155
