The adoptr package provides functionality to explore custom optimal
two-stage designs for one or two-arm superiority tests.
Currently, only (asymptotically) normal test statistics are supported.
adoptr is programmed in an object-oriented way.
A description on object-oriented usage of R can be found
here.
For a sample workflow and a quick demo of the capabilities, see here.
A variety of examples is presented in the validation package adoptrValidation and can be seen here.
adoptr currently supports TwoStageDesign,
GroupSequentialDesign, and OneStageDesign.
Currently, the only implemented data distribution is Normal.
Both ContinuousPrior and PointMassPrior are
supported for the single parameter of a DataDistribution.
An example on working with priors is provided
here.
adoptr provides the score types UnconditionalScore and
ConditionalScore. The conditional scores
ConditionalPower and ConditionalScore are
already implemented. Unconditional scores that are expectations of
conditional scores can be created via expected and are
represented by the class IntegralScore.
For an example how to work with scores, see here.