On 7/7/08, Mary <mlhoward@avalon.net> wrote: > > Yes, and that's what I'm doing in handling the count=0 code; attempt to run > it again with a different parameter,

That is not what I was trying to say at all. If I understand you correctly you "macro" loop over the 10,000 "sets/runs" Getting the results one-at-a-time, check the "status" and try again. This seems too loopy and slow to me. Wouldn't it be better to fit the 10,000 "sets/runs" using BY group processing. Then determine which ones did not "fit" and refit those. You still do it programmaticly just not one-at-a-time.

You will avoid 10,000 SQL steps and 10,000 sets and 10,000 logistics.

It sounds somewhat similar to a simulation where Cassell has shown how much faster the BY group approach is compared to macro looping.

The results would be the same but with fewer steps.

>and if that still doesn't get it to > run, then save the model info to a running data set so that I've got all the > ones that finally didn't run together. This means I've got lots of things > in both blocks of code- attempts at reruns if the code did not run, and > saving of model info, in addition to the output of the things that did run > in my block of code if it did work. > > It is legal in many statistical procedures to just not get ODS output on a > procedure even though the procedure worked- such as odds ratios may not be > appropriate for that particular run, and I'm accumulating a final > spreadsheet of data in which that cell would just be blank, and > appropriately so; it isn't an error in the analysis. The trouble is, > normal SAS output for something like a Proc Logistic can be up to 3 pages > long, and therefore 30,000 pages for 10,000 runs, whereas I want just one > row of output for each run, with perhaps 10,000 rows down. Using the macro > If statements in conjunction with ODS can do this, and it is one of the > reasons why so many genetics people are going over to R, because they don't > think only R can do this, but SAS can, so that's why I brought it up in the > SAS vs. R discussion. > > -Mary > ----- Original Message ----- > From: data _null_, > To: Mary > Cc: SAS-L@listserv.uga.edu > Sent: Monday, July 07, 2008 4:13 PM > Subject: Re: Re: SET with OBS=0 > > On 7/7/08, Mary <mlhoward@avalon.net> wrote: > > The problem with the call execute statement is that it is only one thing, > > instead of allowing me to just handle the condition and move on- usually > I'm > > trying to aggregate 10,000 runs or so- I **don't** want to stop just > because > > one didn't work. > > The call execute(endsas) was an example I don't know exactly what you > are trying to do. I am not following the R thread closely and I did > not read your contributions. > > To me it would seem more efficient to fit all 10,000 "runs" using by > group processing. Then examine the "misfits" and refit them using > different parameters then examine the "misfits" and refit those etc.