Multi.group.test.power: Multi-group test power

In qountstat: Statistical Analysis of Count Data and Quantal Data

Multi-group test power

Description

Idea: Do parametric bootstrapping for each group and evaluate the proportion of significant results.

Usage

Multi.group.test.power(
  groups,
  counts,
  control.name = NULL,
  alpha = 0.05,
  bootstrap.runs = 200,
  use.fixed.random.seed = NULL,
  CPCAT.bootstrap.runs = 200,
  Dunnett.GLM.zero.treatment.action = "log(x+1)",
  show.progress = TRUE,
  show.results = TRUE,
  test = "CPCAT"
)

Arguments

groups	Group vector
counts	Vector with count data
control.name	Character string with control group name (optional)
alpha	Significance level
bootstrap.runs	Number of bootstrap runs
use.fixed.random.seed	Use fixed seed, e.g. 123, for reproducible results. If NULL no seed is set.
CPCAT.bootstrap.runs	Bootstrap runs within CPCAT method
Dunnett.GLM.zero.treatment.action	GLM.Dunnett method to be used for treatments only containing zeros
show.progress	Show progress for each shift of lambda
show.results	Show results
test	Either "CPCAT" or "GLM.Dunnett"

Value

Data frame with results from power analysis

qountstat documentation built on April 4, 2025, 12:18 a.m.