Description Usage Arguments Value Author(s) See Also Examples

View source: R/grouped_csdata_weibull.R

This function does one replication of the simulation for the paper from data generated with Weibull event times and Uniform censoring. It returns a description of the misclassification of both the individual and group tests, the results from the appropriate PAVA, the results from the hybrid EM-PAV algorithm for grouped tests, and the number of iterations the hybrid EM-PAV algorithm takes to converge

1 |

`n` |
number of individuals |

`k` |
grouping size |

`shape` |
shape for the Weibull distribution |

`scale` |
scale for the Weibull distribution (defaults to 1) |

`quantile` |
The maximum probability of the event in the population (default is 0.99) |

`x` |
The maximum value for censoring. This should correspond with the quantile argument. |

`alpha` |
Sensitivity: probability of a positive test results given that the individual is truly diseased (or that the group contains at least one person who is truly diseased). Default is 1 - no misclassification |

`beta` |
Specificity: probability of a negative test results given that the individual is truly not diseased (or that the group contains noone who is truly diseased). Default is 1 - no misclassification |

`t` |
threshold for convergence (default is 0.01) |

`desc.ind` |
Table with description of the misclassification of the individual tests |

`desc.group` |
Table with description of the misclassification of the group tests |

`num.it` |
Number of iterations for the hybrid EM-PAV algorithm to converge |

`ind.result` |
Result from appropriate PAV algorithm ( |

`group.result` |
Result from hybrid EM-PAV algorithm, see function |

Lucia Petito

`hybrid.em.pav`

, `pava.cs.mc`

, `gen.data.weibull.unif`

1 | ```
simulation(100, 2, 4, 25, 0.25, 14, 0.95, 0.95, 0.01)
``` |

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