DOI: 10.5061/dryad.53j96
title: Data from: An R package for analyzing survival using continuous-time open capture-recapture models

description: Capture–recapture software packages have proven to be very powerful tools
 for analysing factors affecting survival in wild populations. However, all
 such packages are limited to discrete-time protocols. Appropriate survival
 analysis tools are still lacking for data acquired from continuous-time
 protocols. We have developed a statistical method and propose an r package
 for analysing such data based on an extension of classical survival
 analysis models incorporating an inhomogeneous Poisson process for
 modelling capture histories. First, data were simulated from a
 continuous-time protocol. These data were used to (i) compare survival
 estimation biases of discrete- and continuous-time approaches and (ii)
 investigate the performance and accuracy of our r package for four types
 of covariates: factors varying between individuals (like sex), in time
 (like climatic factors), both in time and between individuals (like
 physical condition) and age (as a categorical factor). Secondly, the r
 package has been applied to a real data set for survival analysis of cats
 in the Kerguelen archipelago (regrouping 682 cats over 20 years) as an
 illustrative example. Results of the simulated data analysis show that the
 method performs better than its discrete-time counterpart for analysing
 data acquired from continuous-time protocols. It provides unbiased
 parameter estimates for all parameters except those that vary both in time
 and between individuals – which is not surprising, since in our case,
 these factors were not updated in continuous time (i.e. only upon
 capture). When applied to the Kerguelen cat data set, the results suggest
 that survival is lower in juveniles than in adults and subadults, varies
 between study sites and increases with physical condition, and this latter
 effect being more important in females than in males. Sex, season,
 temporal linear trend in survival and the NDVI vegetation index were also
 tested but were not found to be significant. However, confidence intervals
 were too large (due to a low recapture rate) for excluding such effects.
 Further analyses are still needed for rigorous covariate testing in this
 context. In conclusion, continuous-time approaches – such as that
 presented in this paper – should be preferred when data acquired from
 continuous-time protocols is analysed.
description: KERGUELEN
 dataLong–term dataset of
 capture–mark–recapture of feral cats collected at three sites in the
 Grande Terre Island of the Kerguelen archipelago (sub-Antarctic). The
 excel files contains three sheets. The first sheet contains the begining
 and the end of capture sessions and the population in which the capture
 session is performed. The second sheet contains variables that vary in
 time and between the populations. Here the only such variable is the
 Normalized Difference Vegetation Index (NDVI). Date stands for the year in
 which the NDVI is estimated. The last sheet contains information about
 captured individuals: identifier (ind), population (pop), sex (0 for
 females, 1 for males), age (in months), physical condition (PC) and the
 date of capture.