HIV: Epidemiological capture-recapture Data on HIV

In Rcapture: Loglinear Models for Capture-Recapture Experiments

Epidemiological capture-recapture Data on HIV

Description

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

Usage

HIV

Format

15 by 5 numeric matrix, with the following columns:

c1, c2, c3, c4

Capture histories from the four capture occasions

freq

Observed frequencies for each capture history

Details

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

Each row of this data set 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), doi: 10.18637/jss.v019.i05.

Examples

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.

cp.m1 <- closedpCI.t(HIV, dfreq = TRUE, mX = ~ (c1+c2+c3+c4)^2, 
                     mname = "Mt double interaction")
cp.m1
  # The model fits well. Let's find out which interactions are important.
summary(cp.m1$fit)$coefficients
  # Eliminating the non significant interactions stepwise shows that only 
  # the [1,2] interaction is important.

closedpCI.t(HIV, dfreq = TRUE, mX = ~ . + c1:c2, mname = "Mt interaction 1,2")

Rcapture documentation built on May 4, 2022, 5:05 p.m.