Description Usage Arguments Value Examples

View source: R/freedom_functions_2.R

Calculates sample size to achieve specified population sensitivity with population specificity >= specified minimum value, for given population size, cut-point number of positives and other parameters, all paramaters must be scalars

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`N` |
population size |

`sep` |
target population sensitivity |

`c` |
The cut-point number of positives to classify a cluster as positive, default=1, if positives < c result is negative, >= c is positive |

`se` |
test unit sensitivity |

`sp` |
test unit specificity, default=1 |

`pstar` |
design prevalence as a proportion or integer (number of infected units) |

`minSpH` |
minimium desired population specificity |

A list of 2 elements, a dataframe with 1 row and six columns for the recommended sample size and corresponding values for population sensitivity (SeP), population specificity (SpP), N, c and pstar and a dataframe of n rows with SeP and SpP values for each value of n up to the recommended value. Returns sample size for maximum achievable sep if it is not possible to achieve target sep AND SpP>= minSpH.

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RSurveillance documentation built on May 29, 2017, 11:52 p.m.

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