R/ChiSquaredDistribution.R
Pearson2xK-class.RdWhen 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.
Pearson2xK(n_groups)
get_tau_Pearson2xK(p_vector)number of groups considered for testing procedure
vector denoting the event rates per group
pearson <- Pearson2xK(3)
H1 <- PointMassPrior(get_tau_Pearson2xK(c(.3, .25, .4)), 1)