Examples 9.1 - 9.38

Example 9.1: Scatterplots with binning

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