BinomialDataDistribution-class: Binomial data distribution

In kkmann/adoptr: Adaptive Optimal Two-Stage Designs in R

Binomial data distribution

Description

Implements the normal approximation for a test on rates. The reponse rate in the control group, r_C, has to be specified by rate_control. The null hypothesis is: r_E ≤ r_C, where r_E denotes the response rate in the invervention group. It is tested against the alternative r_E > r_C. The test statistic is given as X₁ = √n (r_E - r_C) / √(2 r₀ (1-r₀)), where r₀ denotes the mean between r_E and r_C in the two-armed case, and r_E in the one-armed case.#' All priors have to be defined for the rate difference r_E - r_C.

Usage

Binomial(rate_control, two_armed = TRUE)

## S4 method for signature 'Binomial'
quantile(x, probs, n, theta, ...)

## S4 method for signature 'Binomial,numeric'
simulate(object, nsim, n, theta, seed = NULL, ...)

Arguments

rate_control	assumed response rate in control group
two_armed	logical indicating if a two-armed trial is regarded
x	outcome
probs	vector of probabilities
n	sample size
theta	distribution parameter
...	further optional arguments
object	object of class Binomial
nsim	number of simulation runs
seed	random seed

Details

Note that simulate for class Binomial simulates the normal approximation of the test statistic.

Slots

rate_control

cf. parameter 'rate_control'

See Also

see probability_density_function and cumulative_distribution_function to evaluate the pdf and the cdf, respectively.

Examples

datadist <- Binomial(rate_control = 0.2, two_armed = FALSE)

kkmann/adoptr documentation built on Feb. 3, 2024, 6:55 p.m.