Major changes since the first edition include the following:

  1. Conversion to R  with R used to run all examples in the text
  2. Conversion of the book source into knitr reproducible documents
  3. All code from the text is executable and is on the web site
  4. Use of color graphics and use of the ggplot2 graphics package
  5. New text about problems with dichotomization of continuous variables and with classification (as opposed to prediction)
  6. Expanded material on multiple imputation and predictive mean matching and emphasis on multiple imputation (using the Hmisc aregImpute function) instead of single imputation
  7. Addition of redundancy analysis
  8. A brief survey or new directions in predictive modeling
  9. Added a new section in Chapter 5 on bootstrap confidence intervals for rankings of predictors
  10. Replacement of the U.S. presidential election data with analyses of a new diabetes dataset from NHANES using ordinal and quantile regression
  11. More emphasis on semiparametric ordinal regression models for continuous Y, as direct competitors of ordinary multiple regression, with a detailed case study
  12. A new chapter on generalized least squares for analysis of serial response data
  13. The case study in imputation and data reduction was completely reworked and now focuses only on data reduction, with the addition of sparse principal components
  14. More information about indexes of predictive accuracy
  15. Augmentation of the chapter on maximum likelihood to include more flexible ways of testing contrasts as well as new methods for obtaining simultaneous confidence intervals
  16. Binary logistic regression case study 1 was completely re-worked, now providing examples of model selection and model approximation accuracy
  17. Single imputation was dropped from binary logistic case study 2
  18. The case study in transform-both-sides regression modeling has been reworked using simulated data where true transformations are known, and a new example of the smearing estimator was added
  19. Addition of 222 references, most of them published 2001-2014
  20. New guidance on minimum sample sizes needed by some of the models
  21. De-emphasis of bootstrap bumping for obtaining simultaneous confidence regions, in favor of a general multiplicity approach.