NormalDataDistribution-class: Normal data distribution

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

Normal data distribution

Description

Implements a normal data distribution for z-values given an observed z-value and stage size. Standard deviation is 1 and mean θ √n where θ is the standardized effect size. The option two_armed can be set to decide whether a one-arm or a two-arm design should be computed.

Usage

Normal(two_armed = TRUE)

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

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

Arguments

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 Normal
nsim	number of simulation runs
seed	random seed

Details

See DataDistribution-class for more details.

See Also

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

Examples

datadist <- Normal(two_armed = TRUE)

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