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Title: Calculate Regional Consistency Probabilities for Multi-Regional Clinical Trials
Version: 1.0.0
Description: Provides methods to calculate approximate regional consistency probabilities using Method 1 and Method 2 proposed by the Japanese Ministry of Health, Labor and Welfare (2007) https://www.pmda.go.jp/files/000153265.pdf. These methods are useful for assessing regional consistency in multi-regional clinical trials. The package can calculate unconditional, joint, and conditional regional consistency probabilities. For technical details, please see Homma (2024) <doi:10.1002/pst.2358>.
License: MIT + file LICENSE
Imports: mvtnorm, stats
Suggests: testthat (≥ 3.0.0)
Config/testthat/edition: 3
Encoding: UTF-8
RoxygenNote: 7.3.2
NeedsCompilation: no
Packaged: 2025-05-13 12:27:59 UTC; i_lik
Author: Gosuke Homma [aut, cre]
Maintainer: Gosuke Homma <my.name.is.gosuke@gmail.com>
Repository: CRAN
Date/Publication: 2025-05-15 14:00:06 UTC

Calculate Regional Consistency Probabilities

Description

This function calculates approximate regional consistency probabilities using Methods 1 and 2 proposed by Japanese MHLW (2007). The function can obtain:

For technical details, please see Homma (2024)

Usage

regional.consistency.probs(f.s, PI, alpha, power, seed)

Arguments

f.s

A numeric vector representing the proportion of patients in region s(=1,...,S) among patients in the entire trial population. Values must sum to 1.

PI

A numeric value specifying the threshold for Method 1 (typically set at 0.5).

alpha

A numeric value representing the one-sided level of significance.

power

A numeric value representing the target power.

seed

A random number seed.

Value

A list containing the following components:

f.s

The input proportion of patients in each region

PI

The input threshold value for Method 1

alpha

The input one-sided significance level

power

The input target power

seed

The input seed number

Uncond.Method1

Unconditional regional consistency probability for Method 1

Joint.Method1

Joint regional consistency probability for Method 1

Cond.Method1

Conditional regional consistency probability for Method 1

Uncond.Method2

Unconditional regional consistency probability for Method 2

Joint.Method2

Joint regional consistency probability for Method 2

Cond.Method2

Conditional regional consistency probability for Method 2

Examples

regional.consistency.probs(
  f.s = c(0.1, 0.45, 0.45),
  PI = 0.5,
  alpha = 0.025,
  power = 0.8,
  seed = 123
)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.