get_example_statistics: Generate a list of estimators and p-values to use in examples

In adestr: Estimation in Optimal Adaptive Two-Stage Designs

Generate a list of estimators and p-values to use in examples

Description

This function generates a list of objects of class PointEstimator, IntervalEstimators, and PValues to use in examples of the analyze function.

Usage

get_example_statistics(
  point_estimators = TRUE,
  interval_estimators = TRUE,
  p_values = TRUE
)

Arguments

point_estimators	logical indicating whether point estimators should be included in output list
interval_estimators	logical indicating whether interval estimators should be included in output list
p_values	logical indicating whether p-values should be included in output list

Details

Point estimators

The following PointEstimators are included:

• SampleMean

• PseudoRaoBlackwell

• MedianUnbiasedLikelihoodRatioOrdering

• BiasReduced

Confidence intervals

The following IntervalEstimators are included:

• StagewiseCombinationFunctionOrderingCI

• LikelihoodRatioOrderingCI

P-Values

The following PValues are included:

• StagewiseCombinationFunctionOrderingPValue

• LikelihoodRatioOrderingPValue

Value

a list of PointEstimators, IntervalEstimators and PValue.

Examples

set.seed(123)
dat <- data.frame(
  endpoint = c(rnorm(28, 0.3)),
  stage = rep(1, 28)
)
analyze(data = dat,
        statistics = list(),
        data_distribution = Normal(FALSE),
        design = get_example_design(),
        sigma = 1)

# The results suggest recruiting 32 patients for the second stage
dat <- rbind(
  dat,
  data.frame(
    endpoint = rnorm(32, mean = 0.3),
    stage = rep(2, 32)))
analyze(data = dat,
        statistics = get_example_statistics(),
        data_distribution = Normal(FALSE),
        design = get_example_design(),
        sigma = 1)

adestr documentation built on Sept. 11, 2024, 6:05 p.m.