getN2v2: Number of patients to be enrolled in the second stage

In arsenionhacolo/InferenceBEAGSD: Inference for Binary Endpoint Adaptive Group-Sequential Designs

Description

Calculates the number of patients which should be enrolled in the second stage if the conditional power should be altert to "cp". It's a version of getN2.

Usage

getN2v2(cp, p1, design, k, mode = 0, alpha = 0.05)

Arguments

cp	conditional power to which the number of patients for the second stage should be adjusted.
p1	response probability under the alternative hypothesis.
design	a dataframe containing all critical values for a Simon's two-stage design defined by the colums r1, n1, r, n and p0. r1 = critical value for the first stage (more than r1 responses needed to proceed to the second stage). n1 = number of patients enrolled in the first stage. r = critical value for the whole trial (more than r responses needed at the end of the study to reject the null hypothesis). n = number of patients enrolled in the whole trial. p0 = response probability under the null hypothesis.
k	number of responses observed at the interim analysis.
mode	a value out of 0,1,2,3 dedicating the methode spending the "rest alpha" (difference between nominal alpha level and actual alpha level for the given design). 0 = "rest alpha" is not used. 1 = "rest alpha" is spent proportionally. 2 = "rest alpha" is spent equally. 3 = "rest alpha" is spent only to the worst case scenario (minimal number of responses at the interim analysis so that the study can proceed to the second stage).
alpha	overall significance level the trial was planned for.

Details

This functon is the same as getN2 (OneArmPhaseTwoStudy package), with some changes in arguments' validation. It's is a helper to SimulateSimonDsgnAdaptN.

References

Englert S., Kieser M. Adaptive designs for single-arm phase II trials in oncology. Pharm Stat, 2012, 11, 241-249.

See Also

getN2, SimulateSimonDsgnAdaptN.

Examples

designParam <- CalculateSimonDsgn(0.2, 0.4, 0.05, 0.1)
dsgn <- designParam[designParam$Type == "Optimal",]
getN2v2(0.9, dsgn$p1, dsgn, 7)

arsenionhacolo/InferenceBEAGSD documentation built on May 9, 2019, 4:10 a.m.