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In JMP, how do you adjust the parameterization of categorical variables in a regression model?

lyz6

In JMP, how to adjust the encoding of categorical variables in a regression model?

Accepted answers

jiancao

Creating dummy variables is one approach. But if your model is standard least squares, there is an option called Indicator Parameterization Estimates that does just that.

All comments

Peter_Bartell

lyz6: Can you perhaps provide an example of what you mean by adjusting encoding of categorical variables in a regression model? It's not clear to me what you are trying to accomplish.

shoffmeister

As far as I know, if you want to use dummy-coding instead of effect-coding in your models you will have to create the dummy-variables manually.

In most recent versions of JMP you can do so by "Cols=>Utilities=>Make Indicator Columns". Then use the dummy-variables as factors in your model (of course you should only use all but one).

Hope that helps.

ron_horne

hi lyz6,

try this:

Comparison the results of Standard Least Squares in Fit model with the results of SAS Proc Reg

and then this:

JMP estimates vs. manual calculations

jiancao

Creating dummy variables is one approach. But if your model is standard least squares, there is an option called Indicator Parameterization Estimates that does just that.