My previous blog post shows how to use PROC LOGISTIC and spline effects to predict the probability that an NBA player scores from various locations on a court. The LOGISTIC procedure fits parametric models, which means that the procedure estimates parameters for every explanatory effect in the model. Spline bases
Most SAS regression procedures support the "stars and bars" operators, which enable you to create models that include main effects and all higher-order interaction effects. You can also easily create models that include all n-way interactions up to a specified value of n. However, it can be a challenge to
Last week I discussed ordinary least squares (OLS) regression models and showed how to illustrate the assumptions about the conditional distribution of the response variable. For a single continuous explanatory variable, the illustration is a scatter plot with a regression line and several normal probability distributions along the line. The
