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Nonparametric tests of double-tagging assumptions

Leigh, G. M. and Hearn, W. S. (2018) Nonparametric tests of double-tagging assumptions. Fisheries Research, 197 . pp. 45-49. ISSN 0165-7836

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Article Link(s): https://doi.org/10.1016/j.fishres.2017.09.015

Publisher URL: http://www.sciencedirect.com/science/article/pii/S0165783617302631

Abstract

Shedding rates of tags on fish are commonly estimated from double-tagging experiments, for which an assumption of independence between the two tags on a fish is required. For tags of qualitatively different types, a nonparametric test for this assumption was proposed by Myhre (1966), making use of concurrent double- and single-tagging of fish. We extend Myhre’s test by developing a nonparametric Bayesian test that is also applicable to the common situation where the two tags attached to a fish are identical and assumed to shed at the same rate; the validity of this assumption can be checked by an extra test that we supply in the case that each tag is identified uniquely. In addition to dependence between tags, the dependence test can also be triggered by departures from other experimental assumptions, such as marked variation in the expertise of taggers. We recommend the dependence test for monitoring tag-return data on an ongoing basis during an experiment. We apply our test to Atlantic cod tagging data listed by Barrowman and Myers (1996). Frequentist tests based on Fisher’s Exact Test are also presented.

Item Type:Article
Business groups:Animal Science
Keywords:Bayesian methods Fisher’s Exact Test Monte Carlo simulation Nonparametric statistics Tag dependence Tag shedding
Subjects:Science > Statistics > Statistical data analysis
Aquaculture and Fisheries > Fisheries > Fishery research
Deposited On:12 Jan 2018 05:25
Last Modified:09 Aug 2018 06:03

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