rsu.sssep.rb2st1rf {epiR} | R Documentation |

Calculates the sample size to achieve a desired surveillance system sensitivity assuming risk-based 2-stage sampling on one risk factor at the cluster level, imperfect test sensitivity and perfect test specificity.

rsu.sssep.rb2st1rf(rr, ppr, spr, pstar.c, se.c, pstar.u, se.u, se.p)

`rr` |
vector, defining the relative risk values for each strata in the population. |

`ppr` |
vector of length |

`spr` |
vector of length |

`pstar.c` |
scalar (either a proportion or integer) defining the cluster level design prevalence. |

`se.c` |
scalar proportion, defining the desired cluster level sensitivity. |

`pstar.u` |
scalar (either a proportion or integer) defining the surveillance unit level design prevalence. |

`se.u` |
scalar (0 to 1) representing the sensitivity of the diagnostic test at the surveillance unit level. |

`se.p` |
scalar (0 to 1) representing the desired surveillance system (population-level) sensitivity. |

A list comprised of seven elements:

`n.clusters` |
scalar, the total number of clusters to be sampled. |

`n.clusters.per.strata` |
a vector of the same length as |

`n.units` |
scalar, the total number of units to be sampled. |

`n.units.per.strata` |
a vector of the same length of |

`n.units.per.cluster` |
scalar, the number of units to be sampled from each cluster. |

`epinf` |
a vector of the same length of |

`adj.risk` |
a vector of the same length of |

## EXAMPLE 1: ## A cross-sectional study is to be carried out to confirm the absence of ## disease using risk based sampling. The population of interest is comprised ## of individual sampling units managed within clusters. ## Clusters are stratified into 'high', 'medium' and 'low' risk areas ## where the cluster-level risk of disease in the high risk area compared ## with the low risk area is 5 and the cluster-level risk of disease in ## the medium risk area compared with the low risk area is 3. ## The proportions of the population at risk in the high, medium and low ## risk area are 0.10, 0.20 and 0.70, respectively. The proportion of samples ## taken from the high, medium and low risk areas will be 0.40, 0.40 and ## 0.20, respectively. ## You intend to use a test with diagnostic sensitivity of 0.90 and you'd ## like to take a sufficient number of samples to return a cluster-level ## sensitivity of 0.80 and a population-level (system) sensitivity of 0.95. ## How many units need to be sampled to meet the requirements of the study? rr <- c(5,3,1) ppr <- c(0.10,0.20,0.70) spr <- c(0.40,0.40,0.20) rsu.sssep.rb2st1rf(rr, ppr, spr, pstar.c = 0.01, se.c = 0.80, pstar.u = 0.10, se.u = 0.90, se.p = 0.95) ## A total of 197 clusters needs to be sampled, 79 from the high risk area, ## 79 from the medium risk area and 39 from the low risk area. A total of ## 18 units should be sampled from each cluster, 3546 units in total.

[Package *epiR* version 2.0.31 Index]