R/estforboot_covATE.R

In Yunshu7/dsmatch: Use double score matching algorithm to estimate ATE and QTE

estforboot_covATE <- function(data, indices){
  data1 <- data[indices, ]
  
  dim2 <- dim(data1)[2]
  Y <- data1[, 1]
  A <- data1[, 2]
  Kiw.x <- data1[, 3]
  Yiw.x <- data1[, 4:5]
  X <- data1[, 6:dim2]
  loc.1 <- which(A == 1)
  loc.0 <- which(A == 0)
  
  lm.y <- Y
  lm.x <- cbind(X, t(apply(X, 1, combn, 2, prod)), X ^ 2, X ^ 3)
  
  lm.out1 <- lm(lm.y[which(A == 1)] ~ lm.x[which(A == 1), ])
  # mu1.seive <- cbind(1, lm.x) %*% lm.out1$coefficients
  mu1.x <- cbind(1, lm.x[,which(!is.na(lm.out1$coefficients)) - 1]) %*% lm.out1$coefficients[!is.na(lm.out1$coefficients)]
  sigsqhat1 <- mean((lm.out1$residuals) ^ 2)
  lm.out0 <- lm(lm.y[which(A == 0)] ~ lm.x[which(A == 0), ])
  # mu0.seive <- cbind(1, lm.x) %*% lm.out0$coefficients
  mu0.x <- cbind(1, lm.x[,which(!is.na(lm.out0$coefficients)) - 1]) %*% lm.out0$coefficients[!is.na(lm.out0$coefficients)]
  sigsqhat0 <- mean((lm.out0$residuals) ^ 2)
  
  mu.x <- A * mu1.x + (1 - A) * mu0.x
  
  boot.x <- mean(mu1.x - mu0.x + (2 * A - 1) * (Kiw.x + 1) * (Y - mu.x))
  
  return(boot.x)
}