Hi,
I am looking to pool results after using a macro by @LinusS_ to output hazard ratios for each level of a continuous exposure. The dataset looks something like this:
_imputation_ Exposure Estimate StdErr 1 10 -0.3 0.4 ... ... ... ... 1 60 -0.6 0.2
And so on for each imputation cycle for up to 10 imputed datasets.
I'm a novice when it comes to using PROC MIANALYZE, so I'm not sure how to use it when the dataset I'm trying to pool the data from wasn't created by a SAS PROC. Do I use parm= or data=? Any help would be greatly appreciated!
It's probably easier to use data, I used this code recently:
proc sort data=Estimates; by Label _Imputation_; run; ods select none; proc mianalyze data = Estimates; by Label; modeleffects Estimate; stderr StdErr; ods dataset ParameterEstimates=parms; run;
ods select all;
Note that I use the unexponentiated estimates, since Rubin's rules requires the estimates to be approximately normally distributed, so just exponentiate the results in parms to get HR:s and CI:s.
It's probably easier to use data, I used this code recently:
proc sort data=Estimates; by Label _Imputation_; run; ods select none; proc mianalyze data = Estimates; by Label; modeleffects Estimate; stderr StdErr; ods dataset ParameterEstimates=parms; run;
ods select all;
Note that I use the unexponentiated estimates, since Rubin's rules requires the estimates to be approximately normally distributed, so just exponentiate the results in parms to get HR:s and CI:s.
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