Perform graphical multiple comparison procedures efficiently for power calculation

These functions performs similarly to graph_test_closure() or graph_test_shortcut() but are optimized for efficiently calculating power. For example, generating weights and calculating adjusted weights can be done only once. Vectorization has been applied where possible.

Usage

graph_test_closure_fast(p, alpha, adjusted_weights, matrix_intersections)

graph_test_shortcut_fast(p, alpha, adjusted_weights)

Arguments

p

A numeric vector of one-sided p-values (unadjusted, raw), whose values should be between 0 & 1. The length should match the number of hypotheses in graph.

alpha

A numeric value of the one-sided overall significance level, which should be between 0 & 1. The default is 0.025 for one-sided hypothesis testing. Note that only one-sided tests are supported.

adjusted_weights

The adjusted hypothesis weights, which are the second half of columns from graph_generate_weights() output, adjusted by the appropriate test types (Bonferroni, Simes, or parametric).

matrix_intersections

A matrix of hypothesis indicators in a weighting strategy, which are the first half the graph_generate_weights() output.

Value

A logical or integer vector indicating whether each hypothesis can be rejected or not.

See also

• graph_test_closure() for closed graphical multiple comparison procedures.

• graph_test_shortcut() for shortcut graphical multiple comparison procedures.