15.6. Respiratory Data

In Chapter 14, a repeated measurements analysis of the respiratory data was performed. The response function modeled was the logit, and the response was whether the outcome was good or excellent versus all other responses such as fair, poor, and so on. Explanatory variables included treatment, center, and visit. These data also included other explanatory variables, such as age, sex, and baseline, that couldn’t be handled in the WLS repeated measurements setting because there wasn’t adequate sample size. The GEE method enables you to take such explanatory variables into account.

First, the same model that resulted from the WLS is fit with the GEE method. The WLS strategy is also a marginal method that provides a robust ...

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