HIV {Rcapture}R Documentation

Closed Population Epidemiological Data

Description

Epidemiological capture-recapture data on HIV from four reporting centers in Rome, Italy.

Usage

data(HIV)

Format

c1, c2, c3, c4
Capture histories for the four capture occasions
freq
Observed frequencies for each capture history

Details

The capture histories are obtained by linking the records of the four reporting centers.

This data set's format is the alternative one, i.e. each row represents an observed capture history followed by its frequency.

Source

Abeni, D.A., Brancato, G. and Perucci, C. A. (1994) Capture-recapture to estimate the size of the population with human immunodeficiency virus type 1 infection. Epidemiology, 5, 410–414

References

Baillargeon, S. and Rivest, L.P. (2007). Rcapture: Loglinear models for capture-recapture in R. Journal of Statistical Software, 19(5), http://www.jstatsoft.org/

Examples

data(HIV)
desc<-descriptive(HIV,dfreq=TRUE)
desc
  # 1774 out of 1896 individuals (94%) appear on one list only.

plot(desc)
  # The fi plot is linear showing that heterogeneity is not a problem.  
  # Models with a time (or list) effect and possible pairwise dependencies 
  # between lists will be considered.

mat<-histpos.t(4)
mX1<-cbind(mat,mat[,1]*mat[,2],mat[,1]*mat[,3],mat[,1]*mat[,4],
           mat[,2]*mat[,3],mat[,2]*mat[,4],mat[,3]*mat[,4])
cp.m1<-closedp.mX(HIV,dfreq=TRUE,mX=mX1,mname="Mt double interaction")
cp.m1
  # The model fits well. Let's find out the interactions that are important.
summary(cp.m1$glm)$coefficients
  # Eliminating the non significant interactions stepwise shows that only 
  # the [1,2] interaction is important.

mX2<-cbind(mat,mat[,1]*mat[,2])
closedp.mX(HIV,dfreq=TRUE,mX=mX2,mname="Mt interaction 1,2")
profileCI(HIV,dfreq=TRUE,mX=mX2,mname="Mt interaction 1,2")

[Package Rcapture version 1.1 Index]