Logistic regression or other methods are now more commonly used.

Note: independent variables in logistic regression can also be continuous.

Here logistic regression is being used as a binary classification model.

It is used as a descriptive statistics, and plays an important role in logistic regression.

Discriminant function analysis is very similar to logistic regression, and both can be used to answer the same research questions.

With both continuous and categorical data, it would be best to use logistic regression.

However, when discriminant analysis' assumptions are met, it is more powerful than logistic regression.

Logistic regression is used to predict the odds of being a case based on the predictor(s).

Logistic regression is used extensively in numerous disciplines, including the medical and social science fields.

As such it treats the same set of problems as does logistic regression using similar techniques.