set.seed(123) n <- 160 trt <- factor(rep(0:1, each = n/2)) y <- 4 + (trt == 1) + rnorm(n) z <- matrix(rnorm(n * 2), ncol = 2) dat <- data.frame(y, trt, z) mod <- lm(y ~ trt, data = dat) ## Note that ntree should usually be higher frst <- pmforest(mod, ntree = 20) pmods <- pmodel(frst, fun = identity) ## Note that B should be at least 100 ## The low B is just for demonstration ## purposes. tst <- test_heterogeneity(forest = frst, pmodels = pmods, B = 10) tst$pvalue plot(tst)
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