Recently in the SAS Community Library: SAS' @Sundaresh1 highlights a sometimes overlooked task when applying document embeddings for purposes of similarity-based search. Normalisation of vectors helps obtain relevant matches.
is it possible to output predicted individual-level slopes from proc mixed? Here is my current code. Thanks!
proc mixed data=all covtest cl;
class ptID;
model value=visitYr / s residual outp=pred;
random int visitYr / type=un subject=ptID g gcorr v;
ods output CovParms=covout solutionr=slopes;;
run;
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Hi, I am running the following macro %macro geomeans (data=, outcome=);
%let total_vars = %sysfunc (countw (&outcome) );
%do i = 1 %to &total_vars;
%let selected_var=%scan (&outcome, &i);
ods output estimates=geomeans&i;
proc genmod data=&data;
class brinda15 / param = glm;
model &outcome = brinda15 / type3 dist=normal ;
estimate "Overall estimate &outcome brinda15 =0" intercept 1 brinda15 1 0 /exp;
estimate "Overall estimate &outcome brinda15 =1 " intercept 1 brinda15 0 1 /exp;
run;
ods output close; I call the macro with the following code: %geomeans (data=db, outcome=var1 var2 var3) It works only for the first variable (it doesn't matter which one it is), but for the other variables I the error message below In case it matters, my outcomes are continuous and ln transformed. Any tips of how to fix this are welcome! Thank you
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Hello, I have a variable in my dataset. The categories for this variable are alphanumeric and in character format. For example, they are: A00 to A99, B60 to B89, and so on. Now, I want to list some of them in my SAS syntax: Data want;
set have;
If myvariable in A20 to A45 then myfavourite = 1;
else myfavourite = 0;
run;
Any help would be much appreciated. Thanks.
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