# Partial identification and dependence-robust confidence intervals for capture-recapture surveys

@article{Sun2020PartialIA, title={Partial identification and dependence-robust confidence intervals for capture-recapture surveys}, author={Jinghao Sun and Luk Van Baelen and Els Plettinckx and Forrest W. Crawford}, journal={arXiv: Methodology}, year={2020} }

Capture-recapture (CRC) surveys are widely used to estimate the size of a population whose members cannot be enumerated directly. When $k$ capture samples are obtained, counts of unit captures in subsets of samples are represented naturally by a $2^k$ contingency table in which one element -- the number of individuals appearing in none of the samples -- remains unobserved. In the absence of additional assumptions, the population size is not point-identified. Assumptions about independence…

## One Citation

### Revisiting Identifying Assumptions for Population Size Estimation

- Computer Science, Mathematics
- 2021

This work presents a re-framing of the multiple-systems estimation problem that decouples the specification of the observed-data model from the identifying assumptions, and discusses how log-linear models and the associated no-highest-order interaction assumption fit into this framing.

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