Bug: graph_test_closure() provides inconsistent results between rejections and closed tests

[xidongdxi]

What happened?

When using parametric tests with graph_test_closure(), it is possible that all intersection hypotheses are rejected but $rejected are all FALSE.

Session Information

No response

Reproducible Example

library(graphicalMCP)
hypotheses <- c(0.5, 0.5, 0, 0)
transitions <- rbind(
c(0, 0, 1, 0),
c(0, 0, 0, 1),
c(0, 1, 0, 0),
c(1, 0, 0, 0)
)
g <- graph_create(hypotheses, transitions)

corr_12 <- matrix(0.5, nrow = 2, ncol = 2)
diag(corr_12) <- 1

p_values <- c(0.01347867, 0.01347867, 0.0125, 0.0125)

set.seed(1234)
test_results_parametric <-
graph_test_closure(
g,
p = p_values,
alpha = 0.025,
test_groups = list(1:2, 3:4),
test_types = c("parametric", "bonferroni"),
test_corr = list(corr_12, NA),
test_values = TRUE
)
test_results_parametric$outputs$rejected
test_results_parametric$test_values

[xidongdxi]

library(mvtnorm)
1-pmvnorm(lower = rep(qnorm(min(p_values[1:2])), 2), sigma = corr_12, mean = rep(0, 2), algorithm = GenzBretz(abseps = 1e-6))
pmvnorm(lower = rep(qnorm(min(p_values[1:2])), 2), sigma = corr_12, mean = rep(0, 2), algorithm = GenzBretz(abseps = 1e-6))

round(1-pmvnorm(lower = rep(qnorm(min(p_values[1:2])), 2), sigma = corr_12, mean = rep(0, 2), algorithm = Miwa(steps = 128)), 6) <=0.025
1-pmvnorm(lower = rep(qnorm(min(p_values[1:2])), 2), sigma = corr_12, mean = rep(0, 2), algorithm = Miwa(steps = 128)) <= 0.025