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  1. ''LEGAL NOTICE AND DISCLAIMER''
  2. Abstract
  3. Appendix A. Additional tools for data analysis
  4. Appendix B. Sequence of steps for developing a logistic regression model in R
  5. Appendix C. Sample code used to process the running COPD example
  6. Appendix D. Sample code used to implement the Cox proportional hazard model in the heart failure mortality example
  7. Appendix E.1. Package - data manipulation
  8. Appendix E.2. Package - date arithmetic
  9. Appendix E.3. Package - math functions (re)defined
  10. Appendix E.4. Package - model performance descriptors and graphics
  11. Appendix E.5. Package - plotting utilities
  12. Appendix E.6. Package - statistical functions
  13. Appendix E. R package manuals
  14. Assessing model coefficients
  15. Code review
  16. Code storage
  17. Coding practices
  18. Comparing two datasets
  19. Computing a multivariate odds ratio
  20. Computing a univariate odds ratio
  21. Data scrubbing
  22. Data storage
  23. Evaluating model performance
  24. Footnotes
  25. Formatting and storage of intermediate results
  26. General approach
  27. Including interaction terms in the model
  28. Input data storage
  29. Introduction
  30. LEGAL NOTICE AND DISCLAIMER
  31. Linear regression
  32. Logistic regression
  33. Main Page
  34. Methodology
  35. Model validation
  36. Naming conventions
  37. Nomenclature of input variables
  38. Outliers
  39. Output data naming conventions
  40. Output data storage
  41. Predicting future outcomes
  42. Predictive variable selection
  43. Preferred terminology
  44. Presentation format
  45. Presentation of results
  46. R
  47. Receiver operating characteristics curve
  48. References
  49. Regression
  50. Removing highly correlated variables

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