Comparing models based on log-likelihood values

[aoifeoneill]

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:

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!

[stat_sas]

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]

@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 · Accepted solution]

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]

Yes of course, thanks @stat_sas !