One commonly used analytic technique that examines predictors of a binary outcome (disease/no disease, test positive/test negative, etc.) is called a logistic regression. As it is for other types of regression analyses, the final set of predictors that are added to the regression equation must all be present for each case that is included in the final analysis pool. The most important point when building a model is not to enter all variables in a haphazard fashion. There are specific steps to arriving at the final set of predictors.