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Understanding the impact of correlation within pair-bonds on Cormack-Jolly-Seber models
Alexandru M Draghici1, Wendell O Challenger2, Simon J Bonner1
1Department of Statistical and Actuarial Sciences Western University London Ontario Canada.
Ecology and Evolution
|June 18, 2021
Summary
Correlated survival and recapture fates in mated animals can lead to underestimated standard errors and deflated test statistics in the Cormack-Jolly-Seber (CJS) model, impacting wildlife survival analysis.
Area of Science:
- Ecology
- Wildlife Biology
- Statistical Modeling
Background:
- The Cormack-Jolly-Seber (CJS) model is standard for analyzing animal survival in open populations.
- It assumes independent fates, which is unrealistic for paired animals.
- Pair-bonding suggests correlated survival and recapture probabilities.
Purpose of the Study:
- To extend the CJS model for correlated fates of paired animals.
- To simulate data with varying degrees of survival correlation between mates.
- To assess the impact of correlated fates on CJS model inference.
Main Methods:
- Developed a CJS model extension for pair-bonded animals.
- Generated simulation data with correlated survival and recapture fates.
- Computed Monte Carlo estimates for bias, range, and standard errors.
- Evaluated likelihood ratio tests for sex effects and variance inflation factors.
Main Results:
- Correlated fates lead to underestimated standard errors in parsimonious CJS models.
- Likelihood ratio test statistics for sex effects are significantly deflated.
- Variance inflation factors are underestimated when incorporating sex-specific heterogeneity.
Conclusions:
- Underestimated standard errors reduce confidence interval coverage.
- Deflated test statistics yield overly conservative results.
- Underestimated variance inflation factors can lead to incorrect conclusions about extra-binomial variation.
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