Description Arguments Details Slots Examples

`DataDistribution`

is an abstract class used to represent the distribution
of a sufficient statistic `x`

given a sample size `n`

and a
single parameter value `theta`

.

`x` |
outcome |

`n` |
sample size |

`theta` |
distribution parameter |

`...` |
further optional arguments |

This abstraction layer allows the representation of t-distributions
(unknown variance), normal distribution (known variance), and normal
approximation of a binary endpoint.
Currently, the two implemented versions are `Normal-class`

and
`Binomial-class`

.

The logical option `two_armed`

allows to decide whether a one-arm or
a two-arm (the default) design should be computed. In the case of a two-arm
design all sample sizes are per group.

`two_armed`

Logical that indicates if a two-arm design is assumed.

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