Pearson2xK-class: Pearson's chi-squared test for contingency tables

In adoptr: Adaptive Optimal Two-Stage Designs

Pearson's chi-squared test for contingency tables

Description

When we test for homogeneity of rates in a k-armed trial with binary endpoints, the test statistic is chi-squared distributed with k-1 degrees of freedom under the null. Under the alternative, the statistic is chi-squared distributed with a non-centrality parameter \lambda. The function get_tau_Pearson2xk then computes \tau, such that \lambda is given as n \cdot \tau, where n is the number of subjects per group. In adoptr, \tau is used in the same way as \theta in the case of the normally distributed test statistic.

Usage

Pearson2xK(n_groups)

get_tau_Pearson2xK(p_vector)

Arguments

n_groups	number of groups considered for testing procedure
p_vector	vector denoting the event rates per group

Examples

pearson <- Pearson2xK(3)


H1 <- PointMassPrior(get_tau_Pearson2xK(c(.3, .25, .4)), 1)

adoptr documentation built on Oct. 3, 2024, 1:08 a.m.