Improve Predictions with Powerful Nonlinear Regression Software

SPSS Regression Models enables you to apply more sophisticated models to your data using its wide range of nonlinear regression models. You can apply SPSS Regression Models, an add-on module for SPSS Base, to many disciplines, including:

• Market research: Study consumer buying habits
• Medical research: Study response to dosages through probit analysis
• Institutional research: Measure academic achievement tests
• Loan assessment: Analyze good and bad credit risks

SPSS Regression Models includes these procedures:

• Multinomial logistic regression (MLR): Predict categorical outcomes with more than two categories
• Binary logistic regression: Easily classify your data into two groups
• Nonlinear regression (NLR) and constrained nonlinear regression (CNLR): Estimate parameters of nonlinear models
• Probit analysis: Evaluate the value of stimuli using a logit or probit transformation of the proportion responding

The latest version includes additional diagnostics for use when developing a classification table.