esStat<-function(logw=NULL,
                  w.ctrl=NULL,
                  gbm1=NULL,
                  i=1,
                  data,
                  sampw,
                  rule.summary,
                  na.action="level",
                  vars,
                  treat.var,
                  collapse.by.var=FALSE,
                  verbose=FALSE,
                  estimand)
{
if(!(estimand %in% c("ATT","ATE"))) stop("estimand must be either \"ATT\" or \"ATE\".")

if(estimand=="ATT") 
{

   if(is.null(gbm1) && is.null(w.ctrl) && is.null(logw))
      stop("No weights given. logw, gbm1, and w.ctrl cannot all be NULL.")
   if(!is.null(rule.summary)) rule.summary <- match.fun(rule.summary)
   w1 <- rep(1/sum(data[,treat.var]==1), nrow(data))
   if(is.null(gbm1))
   {
      if (!is.null(logw))
      {
         w.ctrl<-exp(logw)
      }
      w1[data[,treat.var]==0] <- w.ctrl
   } else
   {
      w <- exp(predict(gbm1,newdata=data[data[,treat.var]==0,],
                           n.trees=i))
      w1[data[,treat.var]==0] <- w
   }
   w1 <- w1*sampw

   # compute effect sizes
   es <- lapply(data[,vars], ps.summary,
                t=data[,treat.var],
                w=w1,
                get.means=TRUE,
                get.ks=FALSE,
                na.action=na.action,
                estimand=estimand)

   if(collapse.by.var)
   {
      es <- sapply(es,function(x,rule.summary){rule.summary(x$std.eff.sz,na.rm=TRUE)},
                   rule.summary=rule.summary)
   } else
   {
      es <- unlist(sapply(es,function(x){x$std.eff.sz}))
   }

   if(!is.null(rule.summary))
   {
      if(verbose) print(rule.summary(es,na.rm=TRUE))
      return(rule.summary(abs(es),na.rm=TRUE))
   } else
   {
      return(es)
   }
}

if(estimand=="ATE") 
{
    if (is.null(gbm1) && is.null(w.ctrl) && is.null(logw)) 
        stop("No weights given. logw, gbm1, and w.ctrl cannot all be NULL.")
    if (!is.null(rule.summary)) 
        rule.summary <- match.fun(rule.summary)
    w1 <- rep(1/nrow(data), nrow(data))
    if (is.null(gbm1)) {
        if (!is.null(logw)) {
             w.ctrl <- exp(logw)
        }
        w1[data[, treat.var] == 0] <- w.ctrl
    }
    else {
       w <- exp(predict(gbm1, newdata = data, n.trees = i))/(1+exp(predict(gbm1, newdata = data, n.trees = i)))
        w1[data[, treat.var] == 0] <- 1/(1-w[data[, treat.var] == 0])
	w1[data[, treat.var] == 1] <- 1/(w[data[, treat.var] == 1])
    }
    w1 <- w1 * sampw
    es <- lapply(data[, vars], ps.summary, t = data[, treat.var], 
        w = w1, get.means = TRUE, get.ks = FALSE, na.action = na.action, estimand=estimand)
    if (collapse.by.var) {
        es <- sapply(es, function(x, rule.summary) {
            rule.summary(x$std.eff.sz, na.rm = TRUE)
        }, rule.summary = rule.summary)
    }
    else {
        es <- unlist(sapply(es, function(x) {
            x$std.eff.sz
        }))
    }
    if (!is.null(rule.summary)) {
        if (verbose) 
            print(rule.summary(es, na.rm = TRUE))
        return(rule.summary(abs(es), na.rm = TRUE))
    }
    else {
        return(es)
    }
}

}