Survival estimation and the effects of dependency among animals
Journal of Applied Statistics
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Abstract
Survival models assume that fates of individuals are independent, yet the robustness of this assumption has been poorly quantified. We examine how empirically derived estimates of the variance of survival rates are affected by dependency in survival probability among individuals. We used Monte Carlo simulations to generate known amounts of dependency among pairs of individuals and analyzed these data with Kaplan-Meier and Cormack-Jolly-Seber models. Dependency significantly increased these empirical variances as compared to theoretically derived estimates of variance from the same populations. Using resighting data from 168 pairs of black brant, we used a resampling procedure and program RELEASE to estimate empirical and mean theoretical variances. We estimated that the relationship between paired individuals caused the empirical variance of the survival rate to be 155% larger than the empirical variance for unpaired individuals. Monte Carlo simulations and use of this resampling strategy can provide investigators with information on how robust their data are to this common assumption of independent survival probabilities.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Survival estimation and the effects of dependency among animals |
| Series title | Journal of Applied Statistics |
| DOI | 10.1080/02664769524531 |
| Volume | 22 |
| Issue | 5/6 |
| Year Published | 1995 |
| Language | English |
| Publisher | Taylor & Francis |
| Publisher location | Philadelphia, PA |
| Contributing office(s) | Alaska Biological Science Center |
| Description | 9 p. |
| Larger Work Type | Article |
| Larger Work Subtype | Journal Article |
| Larger Work Title | Journal of Applied Statistics |
| First page | 673 |
| Last page | 681 |
| Google Analytic Metrics | Metrics page |