# sample.def2: using simulation. considering desired conditional assurance... In carolinewei/apsurvival: Total sample size and its allocation for the MRCT

## Description

using simulation. considering desired conditional assurance probability to claim overall consistency and determines optimal sample size allocation across regions by maximizing conditional assurance probability based on Definition 2 if regional treatment effects are slightly different. (Allocate equal sample size to each region if treatment effects across regions are the same.)

## Usage

 ```1 2``` ```sample.def2(r0, alpha = 0.05, beta = 0.2, lamda, lamda_cen, L, s, u, bound, grid = 0.1, n = 1e+05, consistency = 0.8) ```

## Arguments

 `r0` True overall log hazard ratio `alpha` The risk of rejecting the null hypothesis H0:r0>=0 when it is really true `beta` The risk of failing to reject the null hypothesis H0:r0>=0 when it is really false `lamda` The event hazard rate for placebo `lamda_cen` The discontinuation hazard rate `L` The whole study duration of fixed study duration design `s` Number of regions participating in the MRCT `u` A vector presents ratios of true regional log hazard ratios to true overall log hazard ratio r=u*r0 `bound` The given parameter in Definition 2 `grid` Grid interval of the grid research `n` Simulation times `consistency` A numeric value is the desired conditional assurance probability to claim overall consistency showing only two decimal places.

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## Examples

 ```1 2 3``` ```set.seed(123) Sampsize2 <- sample.def2(r0=log(0.7), alpha=0.05, beta=0.2, lamda=1, lamda_cen=1, L=2, s=3, u=c(0.9,1,1.1), bound=(1-0.7)/3, grid=0.1, n=1000, consistency=0.8) ```

carolinewei/apsurvival documentation built on Nov. 4, 2019, 8:44 a.m.