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aoifeoneill
Fluorite | Level 6

Hi,

 

I would like to compare a number of models based on their log-likelihood values. The log-likelihood values are saved in one dataset as follows:

LogL.PNG

A difference of 0.01 between two log-likelihood values is considered to be the same model. I would also like to print the % or number of models that were the same and what observation number it was.

 

Does anyone know if this is possible? Any help with this would be greatly appreciated!

1 ACCEPTED SOLUTION

Accepted Solutions
stat_sas
Ammonite | Level 13

Hi,

 

I think no need to compare each value with all the ramaining ones. First sort data based log_likelihood values then use the syntax. It will make the comparison easier.

 

proc sort data=have;

by  log_likelihood;

run;

 

data want;
set have;
diff = log_likelihood - lag(log_likelihood);
if _n_>1 then do;
if abs(diff)<=0.001 then observation=_n_;
end;
run;

View solution in original post

4 REPLIES 4
stat_sas
Ammonite | Level 13

Hi,

 

Something like this?

 

data want;
set have;
diff = log_likelihood - lag(log_likelihood);
if _n_>1 then do;
   if abs(diff)<=0.001 then observation=_n_;
end;
run;

aoifeoneill
Fluorite | Level 6

@stat_sas to determine the number of models that are the same do you not need to compare likelihood 1 with all other likelihood values, likelihood 2 with all other likelihood values, and so on. Not just the value directly following... maybe I need to loop this?

stat_sas
Ammonite | Level 13

Hi,

 

I think no need to compare each value with all the ramaining ones. First sort data based log_likelihood values then use the syntax. It will make the comparison easier.

 

proc sort data=have;

by  log_likelihood;

run;

 

data want;
set have;
diff = log_likelihood - lag(log_likelihood);
if _n_>1 then do;
if abs(diff)<=0.001 then observation=_n_;
end;
run;

aoifeoneill
Fluorite | Level 6
Yes of course, thanks @stat_sas !

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