1. Relationships in crosstabulations
2. The log-linear model
A. Specifying models
Saturated models
Nonsaturated models
B. Fitting marginals
Generating expected frequencies
C. Analyzing odds
3. Testing for fit
A. How to evaluate models fitted to data
B. Comparisons of different models of the same data
Independence hypothesis
Equal marginal distributions hypothesis
C. More complex models: polytomous variables
D. More complex hypotheses
E. An analog to multiple R² for large samples
4. Applications to substantive problems
A. Causal models for log-linear models
B. Analyzing change over time
Comparative cross-sections
Two-wave panels
Markov chain models
Age, period, and cohort models
5. Special techniques with log-linear models
A. What to do about zero cells
B. Fixing start values
C. Analyzing ordered data
D. Collapsing polytomous variables
E. Nonhierarchical models
6. Conclusions.