Minitab provides three link functions, which allows you to fit a broad class of binary response models. These link functions are the inverse of the cumulative logistic distribution function (logit), the inverse of the cumulative standard normal distribution function (normit), and the inverse of the Gompertz distribution function (gompit).

You want to choose a link function that results in a good fit to your data. Patterns in the residuals versus fits plot or a residuals versus variables plot can show that a link function is not a good fit to your data. You can also use goodness-of-fit statistics to compare fits using different link functions. Certain link functions can be used because of historical reasons or because they have a special meaning in a discipline.

One advantage of the logit link function is that it provides an estimate of the odds ratio for each predictor in the model. For the logit link function, the odds ratios from a retrospective sample estimate the odds ratios from a prospective sample. Retrospective samples are faster to collect than prospective samples.

For the health care center data, investigators used the Logit link function.