sdF.Rdusing wild bootstrap to obtain standard deviation
sdF(B, formla, xformla, data, tvals, h, cl = 1)
| B | number of bootstrap iterations |
|---|---|
| formla | a formula y ~ treatment |
| xformla | one sided formula for x variables to include, e.g. ~x1 + x2 |
| data | the data.frame where y, t, and x are |
| tvals | a grid of values of treatment variable |
| h | bandwidth |
| cl | the number of clusters to use, default is 1 |
sd
data(igm) igm$hs=ifelse(igm$HEDUC=="HS",1,0) igm$col=ifelse(igm$HEDUC=="COL",1,0) formla=lcfincome~lfincome xformla=~hs+col tvals=seq(quantile(igm$lfincome,probs = 0.1),quantile(igm$lfincome,probs = 0.9),length.out = 10) h=1.2 data=igm B=7 sdF(B,formla=formla, xformla=xformla, data=data,tvals=tvals,h=h)#> [1] 0.06397320 0.13758739 0.06336711 0.04779337 0.06097219 0.11789059 #> [7] 0.06824531 0.07012007 0.06705934 0.06595768 #> attr(,"class") #> [1] "sdF"