sse.combined: System sensitivity by combining multiple surveillance...

In RSurveillance: Design and Analysis of Disease Surveillance Activities

Description

Calculates overall system sensitivity for multiple components, accounting for lack of independence (overlap) between components

Usage

sse.combined(C = NA, pstar.c, rr, ppr, sep)

Arguments

C	population sizes (number of clusters) for each risk group, NA or vector of same length as rr
pstar.c	cluster level design prevalence (scalar)
rr	cluster level relative risks (vector, length equal to the number of risk strata)
ppr	cluster level population proportions (optional), not required if C is specified (NA or vector of same length as rr)
sep	sep values for clusters in each component and corresponding risk group. A list with multiple elements, each element is a dataframe of sep values from a separate component, first column= clusterid, 2nd =cluster-level risk group index, 3rd col = sep

Value

list of 2 elements, a matrix (or vector if C not specified) of population-level (surveillance system) sensitivities (binomial and hypergeometric and adjusted vs unadjusted) and a matrix of adjusted and unadjusted component sensitivities for each component

Examples

# example for sse.combined (checked in excel combined components.xlsx)
C<- c(300, 1200)
pstar<- 0.01
rr<- c(3,1)
ppr<- c(0.2, 0.8)
comp1<- data.frame(id=1:100, rg=c(rep(1,50), rep(2,50)), cse=rep(0.5,100)) 
comp2<- data.frame(id=seq(2, 120, by=2), rg=c(rep(1,25), rep(2,35)), cse=runif(60, 0.5, 0.8))
comp3<- data.frame(id=seq(5, 120, by=5), rg=c(rep(1,10), rep(2,14)), cse=runif(24, 0.7, 1))
sep<- list(comp1, comp2, comp3)
sse.combined(C, pstar, rr, sep = sep)
sse.combined(C=NA, pstar, rr, ppr, sep = sep)

Example output

$`System sensitivity`
            Binomial Hypergeometric
Adjusted   0.6679285      0.6773649
Unadjusted 0.7768324      0.7838785

$`Component sensitivity`
, , Binomial

           Component 1 Component 2 Component 3
Adjusted     0.5120273   0.2485273  0.09442829
Unadjusted   0.5120273   0.4066802  0.22919108

, , Hypergeometric

           Component 1 Component 2 Component 3
Adjusted     0.5227986   0.2527514  0.09521634
Unadjusted   0.5227986   0.4118549  0.22996280


$`System sensitivity`
  Adjusted Unadjusted 
 0.6679285  0.7768324 

$`Component sensitivity`
           Component 1 Component 2 Component 3
Adjusted     0.5120273   0.2485273  0.09442829
Unadjusted   0.5120273   0.4066802  0.22919108

RSurveillance documentation built on July 2, 2020, 2:33 a.m.