Dear
I am Hatem Ali.
I have 2 groups of patients, one received basiliximab induction therapy and the other didnt (no induction)
Both groups are not similar in baseline characterestics (10 character) with P value less than o,o5 when comparing both groups
Example:
Characteristics Induction(n=2860) No-induction(n=740) P value
Recipient age (years) 45 41.4 0.0000
Donor age(years) 46.8 43.2 0.0000
Recipient gender (male) 1901 489 0.8423
CIT (Hours) 9.7 14 0.0000
Total HLA mismatch 2.4 1.9 0.0000
To do the propensity score using IPW and then survival curves, I did the following

* Treatment assignment model:
logit induction recipientage donorage gender CIT HLA

* IPW weights:
predict double ps, pr
gen double ipw = 1.induction/ps + 0.induction/(1-ps)

* -stset- data:
stset atime [pw=ipw], fail(fail)

* K-M estimate:
sts graph, survival by(induction)

Now I want to assess the similarity of baseline covariates between treated and untreated subjects in the matched sample or in the sample weighted by the inverse probability of treatment.
How do I do that? and how do I know the number of matched patients in each group?

Final question, Is the weighted sample an ATE weights or ATT weights?

Looking forward to hear back from you