dag_test_MG {ISS}

dag_test_MG

Description

Implements the graph-testing procedures proposed by Meijer and Goeman (2015) for one-way logical relationships. Here implemented for the specific application to isotonic subgroup selection.

Usage

dag_test_MG(
  X0,
  p,
  alpha,
  version = c("all", "any"),
  leaf_weights,
  sparse = FALSE
)

Arguments

X0

a numeric matrix giving points corresponding to hypotheses.

p

a numeric vector taking values in (0, 1] such that length(p) == nrow(X0).

alpha

a numeric value in (0, 1] specifying the Type I error rate.

version

either "all" for the all-parent version of the procedure or "any" for the any-parent version of the procedure.

leaf_weights

optional weights for the leaf nodes. Would have to be a numeric vector of the same length as there are leaf nodes in the DAG (resp. polytree, see sparse) induced by X0.

sparse

a logical value specifying whether X0 should be used to induce a DAG (FALSE) or a polytree (TRUE).

Value

A boolean vector of the same length as p with each element being TRUE if the corresponding hypothesis is rejected and FALSE otherwise.

References

Meijer RJ, Goeman JJ (2015). “A multiple testing method for hypotheses structured in a directed acyclic graph.” Biometrical Journal, 57(1), 123–143.

Examples

X0 <- rbind(c(0.5, 0.6), c(0.8, 0.9), c(0.9, 0.8))
p <- c(0.02, 0.025, 0.1)
alpha <- 0.05
dag_test_MG(X0, p, alpha)
dag_test_MG(X0, p, alpha, version = "any")
dag_test_MG(X0, p, alpha, sparse = TRUE)