BookmarkSubscribeRSS Feed
mftuchman
Quartz | Level 8

I have yet to get an optimal match to run without a failure.   If I have control with M (#cols=VC) and Treatment with N(# cols=VT) (observations, how can I estimate how much resources the optimal match will take?   Every optimal match that I've tried  failed due to non-existence of a good match.  Most variables are binary variables, and distance is defined by LPS (log propensity score).

 

Obviously there are a LOT of factors that would affect the ability to create an optimal match.  Without knowing much more about my data, are there any general guidelines we should be aware of?  Are there any bounds above which an optimal match would be extremely unlikely?

 

Here's my error:

ERROR: A feasible optimal fixed ratio matching that has the specified parameters does not exist.

NOTE: The data set WORK.OUTGS has 0 observations and 87 variables.

NOTE: PROCEDURE PSMATCH used (Total process time):

3 REPLIES 3
mhtoto
Fluorite | Level 6
I am getting the same error? Any suggestions for troubleshooting tips? Many thanks.

proc psmatch data=Preop
region=allobs;
class first20 diseaseseverity site surgeon left_1 female;
psmodel first20= age ;

match method=optimal(k=1) stat=lps caliper=0.9;

assess lps var=(age ) / weight=none plots=(boxplot barchart);
output out(obs=all)=Outgs lps=_Lps matchid=_MatchID;
MichaelL_SAS
SAS Employee

You might try specifying "caliper=." in the match statement to see if the caliper requirement is making the optimal matching infeasible. By default a value of caliper=0.25 is used, so specifying the missing value is necessary to remove the requirement. You can also look at the plots produced by the ASSESS statement to compare the range and distribution of LPS values between the treatment and control condition to see if the caliper might be the cause. 

KK_Mangla
Fluorite | Level 6

Hi,

 

I am facing the similar issue with both OPTIMAL and VARRATIO matching. Is there any method to change the caliper value for optimal with fixed/variable ratio matching. The issue with default value of 0.25 is - it does not give balanced cohorts. Can you suggest me something on this?

Ready to join fellow brilliant minds for the SAS Hackathon?

Build your skills. Make connections. Enjoy creative freedom. Maybe change the world. Registration is now open through August 30th. Visit the SAS Hackathon homepage.

Register today!
What is ANOVA?

ANOVA, or Analysis Of Variance, is used to compare the averages or means of two or more populations to better understand how they differ. Watch this tutorial for more.

Find more tutorials on the SAS Users YouTube channel.

Discussion stats
  • 3 replies
  • 3643 views
  • 3 likes
  • 4 in conversation