In the previous lesson we have covered the basic applications of loglinear models: independence and various types of association. In this lesson we continue with further applications involving ordinal variables and dependent data. Ordinal variables allow for a linear relationship to exist, and we can accommodate with the log-linear model by including a slope parameter interpreted in much the same way as that in a regression model.

The dependent data consideration is the categorical version of matched pairs or repeated measures, where an association between variables is taken for granted, and the questions of interest focus more on the type of agreement between the variables.