Hi, I have a dataset with information on buildings and structural failure risk. I am a bit new to SAS and statistical modelling, so apologies if this is a poor question. data have;
input Buildtype $ RoofType $ Failure $;
datalines;
Detached Mansard No
Detached Flat Yes
Senidetached Pitched No
Apartment Flat No
; I am interested in the probability of failure of different building types and roofs, and the uncertainty estimates of this probability. So far, I have been using proc logistic: proc logistic data=have;
class Buildtype RoofType / param=ref ;
model Failure (event='Yes') = Buildtype RoofType;
Output out=want lower=lower upper=upper predicted=predicted;
run; This outputs: Printed odds ratios and maximum likelihood estimates relative to a reference value. This is useful, but I would like to show a risk of failure relative to the average for all dwellings, if that makes sense. A dataset want that is the same as the have dataset, with predicted failures and confidence intervals added as columns at the end. This is what I want, but is it possible just to get the list of independent variables and their predictions, instead of the entire dataset? The original dataset is quite large...
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