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Diagnostic Goodness-of-Fit Tests for Joint Recapture and Recovery Models

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Diagnostic Goodness-of-Fit Tests for Joint Recapture and Recovery Models. / McCrea, Rachel; Morgan, B.J.T.; Pradel, R.
In: Journal of Agricultural, Biological and Environmental Statistics, Vol. 19, 30.09.2014, p. 338–356.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

McCrea, R, Morgan, BJT & Pradel, R 2014, 'Diagnostic Goodness-of-Fit Tests for Joint Recapture and Recovery Models', Journal of Agricultural, Biological and Environmental Statistics, vol. 19, pp. 338–356. https://doi.org/10.1007/s13253-014-0174-1

APA

McCrea, R., Morgan, B. J. T., & Pradel, R. (2014). Diagnostic Goodness-of-Fit Tests for Joint Recapture and Recovery Models. Journal of Agricultural, Biological and Environmental Statistics, 19, 338–356. https://doi.org/10.1007/s13253-014-0174-1

Vancouver

McCrea R, Morgan BJT, Pradel R. Diagnostic Goodness-of-Fit Tests for Joint Recapture and Recovery Models. Journal of Agricultural, Biological and Environmental Statistics. 2014 Sept 30;19:338–356. Epub 2014 May 8. doi: 10.1007/s13253-014-0174-1

Author

McCrea, Rachel ; Morgan, B.J.T. ; Pradel, R. / Diagnostic Goodness-of-Fit Tests for Joint Recapture and Recovery Models. In: Journal of Agricultural, Biological and Environmental Statistics. 2014 ; Vol. 19. pp. 338–356.

Bibtex

@article{bd016e38aa8548f6b2d5087d9693a037,
title = "Diagnostic Goodness-of-Fit Tests for Joint Recapture and Recovery Models",
abstract = "Diagnostic goodness-of-fit tests for capture–recapture models are routinely used prior to model fitting and analysis. However, when data include a mixture of live recaptures and dead recoveries, it is frequently standard practice for the information from recoveries not to be used, so that tests are applied to the recapture data alone. We present new diagnostic tests for joint recapture–recovery data, which make full use of all of the data, and evaluate their power through simulation. The importance of including all available data is clearly shown. We see in addition that current procedures may fail to identify the correct model. The work is generalised to the case of multi-site joint recapture–recovery data and is illustrated on a data set of great cormorants. This article has supplementary material online.",
keywords = "Contingency tables, Great cormorants, Multi-site models, Parameter redundancy, Permanent emigration, Transience, Trap-effects",
author = "Rachel McCrea and B.J.T. Morgan and R. Pradel",
year = "2014",
month = sep,
day = "30",
doi = "10.1007/s13253-014-0174-1",
language = "English",
volume = "19",
pages = "338–356",
journal = "Journal of Agricultural, Biological and Environmental Statistics",
issn = "1085-7117",
publisher = "Springer New York",

}

RIS

TY - JOUR

T1 - Diagnostic Goodness-of-Fit Tests for Joint Recapture and Recovery Models

AU - McCrea, Rachel

AU - Morgan, B.J.T.

AU - Pradel, R.

PY - 2014/9/30

Y1 - 2014/9/30

N2 - Diagnostic goodness-of-fit tests for capture–recapture models are routinely used prior to model fitting and analysis. However, when data include a mixture of live recaptures and dead recoveries, it is frequently standard practice for the information from recoveries not to be used, so that tests are applied to the recapture data alone. We present new diagnostic tests for joint recapture–recovery data, which make full use of all of the data, and evaluate their power through simulation. The importance of including all available data is clearly shown. We see in addition that current procedures may fail to identify the correct model. The work is generalised to the case of multi-site joint recapture–recovery data and is illustrated on a data set of great cormorants. This article has supplementary material online.

AB - Diagnostic goodness-of-fit tests for capture–recapture models are routinely used prior to model fitting and analysis. However, when data include a mixture of live recaptures and dead recoveries, it is frequently standard practice for the information from recoveries not to be used, so that tests are applied to the recapture data alone. We present new diagnostic tests for joint recapture–recovery data, which make full use of all of the data, and evaluate their power through simulation. The importance of including all available data is clearly shown. We see in addition that current procedures may fail to identify the correct model. The work is generalised to the case of multi-site joint recapture–recovery data and is illustrated on a data set of great cormorants. This article has supplementary material online.

KW - Contingency tables

KW - Great cormorants

KW - Multi-site models

KW - Parameter redundancy

KW - Permanent emigration

KW - Transience

KW - Trap-effects

U2 - 10.1007/s13253-014-0174-1

DO - 10.1007/s13253-014-0174-1

M3 - Journal article

VL - 19

SP - 338

EP - 356

JO - Journal of Agricultural, Biological and Environmental Statistics

JF - Journal of Agricultural, Biological and Environmental Statistics

SN - 1085-7117

ER -