# Sample size for 2-stage risk-based surveillance, allowing for risk factors at either or both cluster and unit level

### Description

Calculates sample size required (clusters and units) for a 2-stage risk-based survey with risk factors at either cluster level or unit level, or both.

### Usage

1 2 | ```
n.rb.2stage.2(rr.c, ppr.c, spr.c, pstar.c, rr.u = 1, ppr.u = 1, spr.u = 1,
pstar.u, se = 1, sep.c = 0.95, sep.sys = 0.95)
``` |

### Arguments

`rr.c` |
relative risk values at the cluster level (vector of values, corresponding to the number of risk strata) |

`ppr.c` |
population proportions at the cluster level, corresponding to rr.c values (vector of equal length to rr.c) |

`spr.c` |
planned surveillance proportions at the cluster level, corresponding to rr.c values - the proportions of the total sample to be collected from each risk stratum (vector of equal length to rr.c). |

`pstar.c` |
cluster (herd) level design prevalence, scalar, either proportion or integer |

`rr.u` |
relative risk values at the unit level (vector of values, corresponding to the number of risk strata) |

`ppr.u` |
population proportions at the unit level, corresponding to rr.u values (vector of equal length to rr.u) |

`spr.u` |
planned surveillance proportions at the unit level, corresponding to rr.u values - the proportions of the total sample to be collected from each risk stratum (vector of equal length to rr.u). |

`pstar.u` |
unit (animal) level design prevalence, scalar, either proportion or integer |

`se` |
unit sensitivity of test (proportion), scalar, default = 1 |

`sep.c` |
desired cluster-level sensitivity (proportion), scalar, default = 0.95 |

`sep.sys` |
desired population-level sensitivity (proportion), scalar, default = 0.95 |

### Value

A list of cluster and unit level results number of clusters/units to sample per risk stratum, the total number of clusters or units per cluster to be sampled and vectors of EPI and adjusted risk values for each risk stratum.

### Examples

1 2 3 4 5 6 7 8 9 10 | ```
rr.c<- c(5,3,1)
ppr.c<- c(0.1, 0.2, 0.7)
spr.c<- c(0.4, 0.4, 0.2)
rr.u<- c(4,1)
ppr.u<- c(0.1, 0.9)
spr.u<- c(1, 0)
n.rb.2stage.2(rr.c, ppr.c, spr.c, pstar.c=0.02, rr.u, ppr.u,
spr.u, 0.1, se=0.9, sep.c=0.5, sep.sys=0.95)
n.rb.2stage.2(c(3,1), c(0.2,0.8), c(0.7,0.3), pstar.c=0.05,
pstar.u=0.1, se=0.9, sep.c=0.95, sep.sys=0.99)
``` |

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