A Sage university paper Quantitative applications in the social sciences ; 20 

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. 

Includes bibliographical references (pages 77-79).