When you enter a column with a nominal modeling type into your model, JMP represents it internally as a set of continuous indicator variables. Each variable assumes only the values –1, 0, and 1. (Note that this coding is one of many ways to use indicator variables to code nominal variables.) If your nominal column has n levels, then n-1 of these indicator variables are needed to represent it. (The need for n-1 indicator variables relates directly to the fact that the main effect associated with the nominal column has n-1 degrees of freedom.) Full details are covered in Nominal Factors in Statistical Details.
Suppose that you have a nominal column with four levels. Take, as an example, the treatment column in the Cholesterol.jmp sample data table. The treatment column has four levels: A, B, Control, and Placebo. Each of the first three levels is represented by an indicator variable. These indicator variables are named treatment[A], treatment[B], and treatment[Control].
The indicator variable for a given level assigns the values 1 to that level, –1 to the last level, and 0 to the remaining levels. Illustration of Indicator Variables for treatment in Cholesterol.jmp shows the definitions of the treatment[A], treatment[B], and treatment[Control] indicator variables for this example. For example, consider the indicator variable treatment[A]. As shown in Illustration of Indicator Variables for treatment in Cholesterol.jmp, this variable assigns values as follows:

Help created on 9/19/2017