SAS programmer since 1981, mostly at Eastman Kodak and Truesense Imaging, Inc., and ON Semiconductor, currently at M&T Bank in beautiful downtown Buffalo, NY. Let's go Buffalo #HornsUp
My bad, left something out, it should be
proc summary data=sashelp.baseball;
var nhits;
output out=stats p90=p90;
run;
data want;
if _n_=1 then set stats;
set sashelp.baseball;
if nhits >= p90 then output;
run;
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proc summary data=have;
var yourvariablename;
output out=stats p90=p90;
run;
data want;
set have;
if yourvariablename >= p90 then output;
run;
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It's a lot easier if you use PROC LOGISTIC instead of PROC GENMOD. There doesn't seem to be a reason in your problem description that you would have to use GENMOD.
proc logistic data=train ... ;
model y = x1 x2 ... ;
score data=train out=trainpreds;
score data=test out=testpreds;
score data=outoftime out=outoftimepreds;
run;
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Using PROC LOGISTIC, see the example named "ROC analysis using separate training and validation data sets" here https://support.sas.com/kb/39/724.html So LOGISTIC does exactly what you want.
This method does not work in PROC GENMOD, and its not clear to me how to do this with PROC GENMOD alone. Probably you will need PROC GENMOD + PROC PLM
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You have to identify the training data in data set PANEL, for example (and there are many ways to do this), let suppose the variable TRAIN has 1 if it is the training data set and has the value 0 otherwise. Then
proc logistic data=panel(where=(train=1)) namelen=60 descending;
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data start_end; /* Determine start and end of event */
set have;
prev_date=lag(date);
prev_event=lag(event);
if date-prev_date>1 then new_event+1;
if event>0 and prev_event=0 then new_event+1;
if event=0 and prev_event>0 then new_event+1;
drop prev:;
run;
proc summary nway data=start_end; /* Determine duration of event */
class new_event;
var event;
output out=by_event max=duration;
run;
data final;
merge start_end by_event;
by new_event;
run;
From now on, please provide data as working SAS data step code (examples and instructions), and not as Excel files, and not as copy/paste from Excel, and not as screen captures.
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@Patrick wrote:
@PaigeMiller I started to copy/paste data provided as tables into Copilot asking for a SAS data step. This often works quite well.
In my opinion, it is the responsibility of the original poster to provide data in usable form if they want code that works; it is not my responsibility to convert it.
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That's how the math works and that's how SAS works, one of the categories will get an estimate of zero. And there's nothing wrong with this answer. I wrote an example to show why this is one way of handling this situation.
https://communities.sas.com/t5/Statistical-Procedures/Interpreting-Multivariate-Linear-Regression-with-Categorical/m-p/591230#M28913
From now on, @acleamon please give more explanation in your first post, do not assume we know what you know.
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Reshaping the data like this only make programming the next step(s) harder. Don't do it.
Tell us what you are going to do with this data after you re-shape it, and we can give you better ideas about how to handle this data.
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Show us what you are looking at that makes you say it isn't right. Explain what you expect to see that would be "right".
Next, no need to compute dummy 0/1 variables like you did, you can perform this regression in PROC GLM without creating dummy 0/1 variables.
proc glm data=capsizedd;
class capsize;
model return=capsize/solution;
run;
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/* UNTESTED CODE */
proc summary data=have3 nway;
class id;
var enddate;
output out=counts nmiss=nmiss;
run;
data want3;
merge have3 counts(drop=_type_ _freq_);
by id;
if nmiss=0 then enddate1=enddate;
run;
The code above is UNTESTED since your data is not in a usable form. From now on, please provide data as text in working SAS data step code (examples and instructions). We cannot work with Excel files, screen captures, or copy/paste from Excel,
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data want;
merge abstractor:;
by population shtmeasure service;
run;
This assumes all data sets are sorted by POPULATION SHTMEASURE SERVICE
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