Hello all, I have a dataset with several variables v1...vn and five groups f1...fn. For each group I took a subset of the data f1<-subset(data,f==1) f2<-subset(data,f==2) and bootstrapped the weighted mean for v1...vn, which worked nicely. data.boot<-boot(f1$v1,mymean,R=2000) Afterwards I combined all boot.out$t for each group: boot$f1v1<-data.boot$t data.boot<-boot(f1$v2,mymean,R=2000) boot$f1v2<-data.boot$t ... data.boot<-boot(f2$v1,mymean,R=2000) boot$f2v1<-data.boot$t ... Each row of boot is used as input in a model resulting in boot$W. My idea is to find (bootstrap) CIs for W. Sorry, I'm new to bootstrap (and R...): Does it make sense to treat the Ws like a bootstrapped variable (and calculate e.g. BCa CIs), because only v1..vn are bootstrapped? If yes, how is a boot object build on the basis of boot$W? I'm aware that boot() handles strata, weights and complex functions, but I didn't manage to get my model bootstrapped right. Hopefully, I can circumvent turning my script upside down. Daniel