I am trying to find the difference in means in my two samples. The distribution is not normal hence I have to resort to Mann Whitney test. Now, the data is weighted. In proc t-test, there is an option of mentioning weight in the command, like this:
proc ttest data=input;
var variable_x;
class variable_y;
weight weight;
run
Is there a similar thing for Mann Whitney test in npar1way procedure? Thanks!
There is no WEIGHT statement, but there is a FREQ statement.
If you have a variable, say NSUBJECTS, that gives an integer number of subjects providing the actual frequency of occurance of the with the corresponding value of the test variable, then you can use this:
FREQ nsubjects ;
Actually, I am using a non-parametric test after doing a case control matching. My case control matching is 1:N in nature, and hence I get weights for each control and case observation. Now, having this information, do you think if I include my matching weights in FREQ option, it would suffice?
No, I do not think FREQ would suffice instead of WEIGHJT
In most parametric tests, FREQ will increase the degrees of freedom, since it is specifying an actual count of cases observed. WEIGHT can control your estimate of a statistic, but since it is more like a sampling fraction concept, it should not (as I understand it) change the degrees of freedom. There's a FREQ statement in TTEST, as well as a WEIGHT statement - pretty direct evidence that they are NOT substituable. Try your ttest twice, once using WEIGHT, once using FREQ.
I suspect the same considerations are true for non-parametric tests. If one wanted to provide a WEIGHT statement in PROC NPAR1WAY, how would the procedure calculate the weighted statistic?
This is all from my ancient and only partially-remembered grad student days when I had a share of statistics classes. Given how ancient that time is, you should probably give a relatively low "weight" to this response, until somebody more knowledgeable replies.
Thank you @Reeza
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!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.