Hi,
I am using logistic regresion to predict a target var type (1,0).
One of the vars of my model is a classificarion var.
a_type = ("high", "medium" , "low"), is a prediction var, not the target
I use proc logistics.
I don't know if it is recommended to transform this var in dummy vars like that:
a_type_high = (1,0)
a_type_medium = (1,0)
a_type_low = (1,0)
I suppose that kind of vars are better for logistic regression, isn't it?
If I don't transform the vars, does the proc do the transformation automatically?
Another question I also have several continuos/quantitative vars like sales (0-50), mkt_exp (0-1000)
do I have to no a normalization to transform in a var with avg=0 and std = 1?, is that needed?
Thanks
Categorical variables should be placed in the CLASS statement.
If it's your first time doing an analysis I like to find a worked example, work through that, then proceed to my data.
The documentation has a good example of analysis with categorical predictors.
Another resource:
http://www.ats.ucla.edu/stat/sas/dae/logit.htm
Normalization is up to you. If you choose to do so, look at proc stdize.
Are res you using SAS Enterprise Miner?
Thanks, I am using Enterprise Guide, no Miner.
I am not sure, when to standarize or not.
Thanks for your help
In the CLASS statement, look at the parameterization options. AFAIK param = Ref is the most common, and most easily interpretable way of specifying your variables. Make sure you review the design matrix and understand your output.
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