Description Usage Arguments Value References Examples

View source: R/Rfun_solveAlphaXsampleSize.R

This function computes the sample size and the error rate pre-assigned to the primary endpoint using methods of `trigger`

, `holm`

, `maurer-bretz`

, `bonferroni`

.

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`alpha` |
a number of overall type I error rate |

`beta0` |
a number of type II error rate for H0 |

`beta1` |
a number of type II error rate for H1 |

`effsz0` |
a number of the effect size of testing H0 |

`effsz1` |
a number of the effect size of testing H1 |

`szratio` |
a number of the ratio of sample size of testing H0 to that of testing H1 |

`t0` |
a vector of information times for H0 |

`t1` |
a vector of information times for H1 |

`tc0` |
a vector of calendar times for H0 |

`tc1` |
a vector of calendar times for H1 |

`rho` |
a value of correlation coefficient between H0 and H1 |

`iuse0` |
an integer shows the type of group sequential boundaries used for the primary endpoint |

`iuse1` |
an integer shows the type of group sequential boundaries used for the secondary endpoint |

`phi0` |
a parameter for the power family or the HSD gamma family for the primary endpoint |

`phi1` |
a parameter for the power family or the HSD gamma family for the secondary endpoint |

`usingRhoForBoundary` |
an indicator whether using the informaiton of rho to calculate the boundary, default is FALSE (not using) |

`method` |
a text of method, including |

`myinit` |
a vector of two starting points for alpha0 and sample size. |

a list of two values, `alpha0`

and `groupsize`

Gou, J. (2021). Sample size optimization and initial allocation of the significance levels in group sequential trials with multiple endpoints. Technical report.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 | ```
# Single Stage Example
alpha <- 0.025
effsz0 <- 0.4
effsz1 <- 0.30
szratio <- 1
beta0 <- 0.10
beta1 <- 0.20
solveAlphaXsampleSize(alpha, beta0, beta1,
effsz0, effsz1, szratio)
# Multi-stage example
alpha=0.025
beta0=0.10
beta1=0.20
effsz0=0.33
effsz1=0.30
szratio=1
t0=c(0.5,0.9,1)
t1=c(0.6,1)
tc0=c(1,2)
tc1=c(1,2,3)
rho=0
iuse0=1
iuse1=2
phi0=-4
phi1=1
usingRhoForBoundary=FALSE
myinit=c(300,alpha/2)
myinit=c(200,alpha/10)
method="trigger"
method="bonferroni"
method="holm"
method="maurer-bretz"
solveAlphaXsampleSize(alpha=alpha,
beta0=beta0, beta1=beta1,
effsz0=effsz0, effsz1=effsz1,
szratio=szratio,
t0=t0, t1=t1, tc0=tc0, tc1=tc1,
rho=rho, iuse0=iuse0, iuse1=iuse1,
phi0=phi0, phi1=phi1,
usingRhoForBoundary=usingRhoForBoundary,
method=method,
myinit=myinit)
``` |

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