Description Usage Arguments Examples

Fit the MEM model for single subgroup using full Bayesian inference.

1 2 3 |

`responses` |
the number of responses in each basket. |

`size` |
the size of each basket. |

`name` |
the name of each basket. |

`drug_index` |
the index of the basket to be studied. |

`p0` |
the null response rate for the poster probability calculation (default 0.15). |

`shape1` |
the first shape parameter(s) for the prior of each basket (default 0.5). |

`shape2` |
the second shape parameter(s) for the prior of each basket (default 0.5). |

`prior` |
the matrix giving the prior inclusion probability for each pair of baskets. The default is on on the main diagonal and 0.5 elsewhere. |

`hpd_alpha` |
the highest posterior density trial significance. |

`alternative` |
the alternative case definition (default greater) |

`call` |
the call of the function (default NULL). |

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ```
# 6 baskets, each with enrollement size 5
trial_sizes <- rep(25, 6)
# The response rates for the baskets.
resp_rate <- 0.15
# The trials: a column of the number of responses and a column of the
# the size of each trial.
trials <- data.frame(
responses = rbinom(trial_sizes, trial_sizes, resp_rate),
size = trial_sizes,
name = letters[1:6]
)
mem_single(trials$responses, trials$size, trials$name, drug_index = 2)
``` |

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