The Fit Model platform gives you an efficient way to specify models that have complex effect structures. These effect structures are linear in the predictor variables. Once you have specified your model, you can select the appropriate fitting technique from a number of fitting personalities. Once you choose a personality, the Fit Model window provides choices that are relevant for the chosen personality. This chapter focuses on the elements of the Model Specification window that are common to most personalities. For a description of all personalities, see Fit Model Launch Window Elements.
Fit Model can be used to specify a wide variety of models that can be fit using various methods. Standard Model Types lists some typical models that can be defined using Fit Model. In the table, the effects X and Z represent columns with a continuous modeling type, while A, B, and C represent columns with a nominal or ordinal modeling type.
Refer to the section Examples of Model Specifications and Their Model Fits to see the clicking sequences that produce these model effects, plots of the model fits, and some examples.
X, X*X, ..., Xk, Z, Z*Z, ..., Zk