nsims <- 100000
N <- 1000
dat <- matrix(data=rnorm(N*nsims, 0), nrow=N, ncol=nsims)
theta.hat <- apply(dat, 2, mean) # theta hat for all obsns
theta.hat.s1 <- apply(dat[1:(N/2), ], 2, mean) # theta hat for S1 data
theta.hat.s2 <- apply(dat[((N/2)+1):N, ], 2, mean) # theta hat for S2 data
early.stopped <- theta.hat.s1 < 0 # index of early-stopped trials
theta.hat.s1.early.stop <- theta.hat.s1[early.stopped] # theta hat, S1 data, early stopped
mean(theta.hat.s1.early.stop)
#> [1] -0.0357289
theta.hat.s1.continue <- theta.hat.s1[!early.stopped] # theta hat, S1 data, continued
mean(theta.hat.s1.continue)
#> [1] 0.03578531
theta.hat.s2.continue <- theta.hat.s2[!early.stopped] # theta hat, S2 data, continued
mean(theta.hat.s2.continue)
#> [1] -0.0002334469
mean(theta.hat[!early.stopped])
#> [1] 0.01777593