Learn R Programming

esDesign (version 1.0.3)

SSR.CP: Calculate the \(N2\) and the critical value \(C\) in Sample Size Re-estimation Procedure

Description

The SSR.CP() is used to calculate the sample size required at the second stage and the critical value used at the final analysis. In addition, this function can also used to conduct the conditional power analysis in terms of \(N2\)

Usage

SSR.CP(Z1 = NULL, delta = NULL, N1 = NULL, pstar, alpha, beta, N2 = NULL)

Arguments

Z1

The test statistic obtained at the interim analysis

delta

The standardized size of treatment effect, which can be estimated by using \((\mu_{X} - \mu_{Y})/\sqrt{\sigma^2}\).

N1

The sample size used at the first stage

pstar

The (1 - power) of accepting the null hypothesis at the interim analysis.

alpha

The overall Type I error rate

beta

The (1 - Power)

N2

The pre-specified sample size used at the second stage, which is used to conduct the conditional power analysis

Value

A list contains

  • N2 The pre-specified sample size used at the second stage, which is used to implement the conditional power analysis

  • Conditional.Power The value of conditional power given the value of N2 in the conditional power analysis

  • P.Value The corresponding P-Value used at the final analysis in the conditional power analysis

  • N2.CP The re-estimated sample size of N2 to ensure an adequate conditional power

  • c.CP The estimated the critical value used at the final analysis based the conditional power

References

  • Proschan MA, Hunsberger SA. Designed extension of studies based on conditional power. Biometrics 1995:1315-1324. <doi:10.2307/2533262>

Examples

Run this code
# NOT RUN {
Z1 <- 1.527
delta <- 0.137
N1 <- 248
pstar <- 0.15
alpha <- 0.05
beta <- 0.2
res <- SSR.CP(Z1 = Z1, delta = delta, N1 = N1,
       pstar = pstar, alpha = alpha, beta = beta)

# }

Run the code above in your browser using DataLab