1. Introduction & overview
1.1 Overview: Categorical data & graphics
1.2 Discrete distributions
1.3 Testing association

berkeleyfreq.sas
sexfuncmh.sas

sexfunchisq.R []

2. Twoway and nway tables
2.1 2 x 2 tables
2.2 Twoway tables
2.3 Observer agreement
2.4 Correspondence analysis

berk4fold.sas
visionsieve.sas
msdiagagree.sas
mentalca.sas

berk4fold.R []
visionsieve.R []
msdiagagree.R []
mentalca.R []

3. Mosaic displays & loglinear models
3.1 nway tables: Models & graphs
3.2 Mosaics software
3.3 Structured tables

berkeleyglm.sas
titanicloglin.sas
mentgen2.sas
visionquasi.sas

berkeleyglm.R []
titanicloglin.R []
mentalglm.R []
visionquasi.R []

4. Logit models & logistic regression
4.1 Logit models
4.2 Logistic regression models
4.3 Effect plots
4.4 Influence & diagnostic plots

berkeleylogit.sas
arthritislogistic.sas
cowleslogistic.sas
Arrestslogistic.sas
cowleseffect.sas
Arrestseffect.sas
berkeleydiag.sas
berkeleydiagods.sas

berkeleylogit.R []
arthritislogistic.R []
cowleslogistic.R []
Arrestslogistic.R []
cowleseffect.R []
Arrestseffects.R []
berkeleydiag.R []
arthritisdiag.R []

5. Polytomous response models
5.1 Proportional odds models
5.2 Nested dichotomies
5.3 Generalized logits

arthritispropodds.sas
arthritispropoddsods.sas
wlfnested.sas
wlfglogit.sas

arthritispropodds.R []
wlfnested.R []
wlfglogit.R []
