Example 9.2: Transparent overplotting and bivariate KDE
Example 9.3: Contingency table plots
Example 9.4: Proc MI and fully conditional specification
Example 9.5: Finite mixture models with concomitant variables
Example 9.6: Model comparison plots (Completed)
Example 9.7: New stuff in SAS 9.3-- Frailty models
Example 9.8: New stuff in SAS 9.3-- Bayesian random effects models in Proc MCMC
Example 9.9: Simplifying R using the mosaic package (part 1)
Example 9.10: more regression trees and recursive partitioning with "partykit"
Example 9.11: Employment plot
Example 9.12: simpler ways to carry out permutation tests
Example 9.13: Negative binomial regression with proc mcmc
Example 9.14: confidence intervals for logistic regression models
Example 9.15: Bar chart with error bars ("Dynamite plot")
Example 9.16: Small multiples
Example 9.17: (much) better pairs plots
Example 9.18: Constructing the fastest relay team via enumeration
Example 9.19: Demonstrating the central limit theorem
Example 9.20: visualizing Simpson's paradox
Example 9.21: The birthday "problem" re-examined
Example 9.22: shading plots and inequalities
Example 9.23: Demonstrating proportional hazards
Example 9.24: Changing the parameterization for categorical predictors
Example 9.25: It's been a mighty warm winter? (Plot on a circular axis)
Example 9.26: More circular plotting
Example 9.27: Baseball and shrinkage
Example 9.28: creating datasets from tables
Example 9.29: the perils of for loops
Example 9.30: addressing multiple comparisons
Example 9.31: Exploring multiple testing procedures
Example 9.32: Multiple testing simulation
Example 9.33: Multiple imputation, rounding, and bias
Example 9.34: Bland-Altman plots
Example 9.35: Discrete randomization and formatted output
Example 9.36: Levene's test for equal variances
Example 9.37: (Mis)behavior of binomial confidence intervals
Example 9.38: dynamite plots, revisited
