CPCAT.power: CPCAT power

In qountstat: Statistical Analysis of Count Data and Quantal Data

CPCAT power

Description

The basic idea of CPCAT power calculations is to do parametric bootstrapping for each dose/concentration group and to evaluate the proportion of results significantly different from the control.

Usage

CPCAT.power(
  groups,
  counts,
  control.name = NULL,
  alpha = 0.05,
  bootstrap.runs = 200,
  use.fixed.random.seed = NULL,
  CPCAT.bootstrap.runs = 200,
  show.progress = TRUE,
  show.results = TRUE
)

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
show.progress	Show progress for each shift of lambda
show.results	Show results

Value

Data frame with results from power analysis

Examples

Daphnia.counts	# example data provided alongside the package

# Test CPCAT power
CPCAT.power(groups = Daphnia.counts$Concentration,
		   counts = Daphnia.counts$Number_Young,
		   control.name = NULL,
		   alpha = 0.05,
		   bootstrap.runs = 10,		# Caution: low number of bootstrap runs for testing
		   use.fixed.random.seed = 123,  #fixed seed for reproducible results
		   CPCAT.bootstrap.runs = 10,# Caution: low number of bootstrap runs for testing
		   show.progress = TRUE,
		   show.results = TRUE)

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