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adoptr

Adaptive optimal two-stage designs for clinical trials with one or two arms for details on the core theoretical background, see:

Pilz M, Kunzmann K, Herrmann C, Rauch G, Kieser M. A variational approach to optimal two-stage designs. Statistics in Medicine. 2019;1–13. https://doi.org/10.1002/sim.8291

Installation

Install the latest CRAN release via

install.packages("adoptr")

and the development version directly from GitHub with:

devtools::install_github("kkmann/adoptr")

Documentation

The documentation is hosted at https://kkmann.github.io/adoptr.

Validation Report

We provide an extensive validation report for adoptr which is implemented using the bookdown package. The sources are available at https://github.com/kkmann/adoptr-validation-report and the last build version is hosted at https://kkmann.github.io/adoptr-validation-report.

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Version

Install

install.packages('adoptr')

Monthly Downloads

416

Version

0.2.2

License

MIT + file LICENSE

Issues

2

Pull Requests

3

Stars

8

Forks

7

Maintainer

Kevin Kunzmann

Last Published

July 2nd, 2019

Functions in adoptr (0.2.2)

ConditionalSampleSize-class

(Conditional) Sample Size of a Design
Constraints

Formulating Constraints
Normal-class

Normal data distribution
bounds

Get support of a prior or data distribution
OneStageDesign-class

One-stage designs
composite

Score Composition
ContinuousPrior-class

Continuous univariate prior distributions
N1-class

Regularize n1
GroupSequentialDesign-class

Group-sequential two-stage designs
adoptr

Adaptive Optimal Two-Stage Designs
plot,TwoStageDesign-method

Plot TwoStageDesign with optional set of conditional scores
n1

Query sample size of a design
get_lower_boundary_design

Boundary designs
minimize

Find optimal two-stage design by constraint minimization
make_tunable

Fix parameters during optimization
condition

Condition a prior on an interval
Prior-class

Univariate prior on model parameter
expectation

Expected value of a function
PointMassPrior-class

Univariate discrete point mass priors
DataDistribution-class

Data distributions
cumulative_distribution_function

Cumulative distribution function
Scores

Scores
TwoStageDesign-class

Two-stage designs
simulate,TwoStageDesign,numeric-method

Draw samples from a two-stage design
predictive_pdf

Predictive PDF
probability_density_function

Probability density function
subject_to

Create a collection of constraints
posterior

Compute posterior distribution
c2

Query critical values of a design
tunable_parameters

Switch between numeric and S4 class representation of a design
predictive_cdf

Predictive CDF
AverageN2-class

Regularization via L1 norm
ConditionalPower-class

(Conditional) Power of a Design