One advantage of the logit link function is that it provides an estimate of the odds ratio for each predictor in the model. The larger the odds ratio, the greater are the odds of a predictor impacting the binary response relative to the predictor's reference level. An odds ratio of 1 indicates no association between the predictor and response.

For the cereal data, the logit link was used, therefore the odds ratios can be interpreted as:

·    an adult who has viewed the advertisement has an odds 2.813 times larger of purchasing Cocoa Crunch than a subject who has not viewed the advertisement (assuming common values for the other variables). Note that the reference level for ViewAd is No.

·    an adult who has children has an odds 4.190 times larger of purchasing Cocoa Crunch than a subject who does not have children (assuming common values for the other variables). Note that the reference level for Children is No.

·    an adult with a household income one thousand dollars (one unit) greater than another subject has an odds 1.014 times greater of purchasing Cocoa Crunch (assuming common values for the other variables). However, the relatively large p-value suggest that this association is not important. You would probably exclude this predictor and refit the model.