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get_xy <- function(n_obs, n_vars, type = c('right', 'left', 'none', 'interval'), standardize=std, positive=F) {
type <- match.arg(type)
x <- matrix(rnorm(n_obs * n_vars), n_obs, n_vars)
y <- rnorm(n_obs)
y_u <- rnorm(n_obs)
# standardize x and y
if (standardize == T) {
for (i in 1:ncol(x)) {
x[, i] <- (x[, i] - mean(x[, i])) / sd(x[, i]);
}
y <- (y - mean(y))
y <- y / sd(y)
if (type == 'interval') {
y_u <- (y_u - mean(y_u))
y_u <- y_u / sd(y_u)
}
}
if (positive) {
y <- abs(y)
y_u <- abs(y_u)
}
if (type == "none") {
status = rep(1, length(y))
y_surv <- Surv(time = y, event = status, type = "right")
} else if (type == 'interval') {
status <- sample(c(0, 1, 2, 3), size=n_obs, replace=T)
y <- cbind(y, y_u)
y <- t(apply(y, 1, sort)) # make sure intervals are increasing in time
y_surv <- Surv(time=y[, 1], time2=y[, 2], event = status, type = 'interval')
} else { # left or right censored
status <- sample(c(0, 1), size=n_obs, replace=T)
y_surv <- Surv(time = y, event = status, type = type)
}
# get the y matrix
y <- cbind(y, y)
if (type=="right") {
y[status == 0, 2] = NA
} else if (type == 'interval') {
y <- NA # NOTE: Not implemented, not needed, use the Surv object!
} else {
y[status == 0, 1] = NA
}
return (list("x" = x, "y" = y, "surv" = y_surv))
}