Calculates population sensitivity for a finite population and allowing for imperfect test sensitivity and specificity, using Freecalc method

1 | ```
sep.freecalc(N, n, c = 1, se, sp = 1, pstar)
``` |

`N` |
population size (scalar) |

`n` |
sample size (scalar) |

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

`se` |
test unit sensitivity (scalar) |

`sp` |
test unit specificity, default=1 (scalar) |

`pstar` |
design prevalence as a proportion - assumed or target prevalence for detection of disease in the population (scalar) |

population-level sensitivity

1 2 3 | ```
# examples of sep.freecalc
sep.freecalc(150, 30, 2, 0.9, 0.98, 0.1)
sep.freecalc(150, 30, 1, 0.9, 0.98, 0.1)
``` |

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