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  1. ''LEGAL NOTICE AND DISCLAIMER''
  2. Abstract
  3. Appendix B. Sequence of steps for developing a logistic regression model in R
  4. Appendix E.1. Package - data manipulation
  5. Appendix E.2. Package - date arithmetic
  6. Appendix E.3. Package - math functions (re)defined
  7. Appendix E.4. Package - model performance descriptors and graphics
  8. Appendix E.5. Package - plotting utilities
  9. Appendix E.6. Package - statistical functions
  10. Assessing model coefficients
  11. Code review
  12. Code storage
  13. Comparing two datasets
  14. Computing a multivariate odds ratio
  15. Computing a univariate odds ratio
  16. Data scrubbing
  17. Evaluating model performance
  18. Footnotes
  19. Formatting and storage of intermediate results
  20. Including interaction terms in the model
  21. Input data storage
  22. LEGAL NOTICE AND DISCLAIMER
  23. Linear regression
  24. Logistic regression
  25. Model validation
  26. Naming conventions
  27. Nomenclature of input variables
  28. Outliers
  29. Output data naming conventions
  30. Output data storage
  31. Predicting future outcomes
  32. Predictive variable selection
  33. Preferred terminology
  34. Presentation format
  35. R
  36. Receiver operating characteristics curve
  37. References
  38. Regression
  39. Removing highly correlated variables
  40. Revision control
  41. Summary of model performance metrics
  42. Survival modeling
  43. Testing and QA
  44. Testing proportions
  45. Transformation of variables
  46. Using logistic regression for classification problems
  47. Validation of temporal datasets
  48. Writing quality code

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