Thanks, Bob. I’ll definitely look into that. It’s an approach I hadn’t
From: qfish-bounce@xxxxxxxxxxxxx [mailto:qfish-bounce@xxxxxxxxxxxxx] On Behalf ;
Of Robert O'Boyle
Sent: Wednesday, January 25, 2017 9:07 PM
Subject: [qfish] Re: correcting for bias in gear characterization study
You can get guidance from Paul Conn's hierarchical analysis of noisy survey
data (Can J FAS 2010 67: 108 -120). While he uses a Bayesian approach, a
state-space approach is also possible. An unobserved abundance is sampled by a
suite of survey gears, which produces a suite of noisy time series. In your
problem, each set of your survey represents a progression of the unoberved
abundance over a a short time period, involving different times of day. You
could have coefficients for each time of day. Each set is then sampled by gear
from each side of the vessel. You could consider the port and starboard sets as
representing separate survey indices with distinct catchability coefficents and
CVs. A state space approach would allow estimate of the time of day
coefficients (and associated CV) and port/starboard coefficients (and
associated CV). Paul's paper gives some guidance on how this problem can be
Hope this helps.
On 23 January 2017 at 08:48, Lee, Laura
This is not a stock assessment question, but I felt the audience of this
listserv would have the answer.
Some background…the study is a gear characterization project looking at paired
hauls from a trawling vessel to compare catches in the experimental net to
those of the control net. We are looking at three different experimental gears.
Ideally, the control and experimental nets are swapped between the port and
starboard sides so that each gear (control or experimental) tows on each side
the same number of times as the other gear. This was not always the case. For
example, in testing of one of the gears, the control gear was on the port side
20 times and on the starboard side 4 times. If there is a side bias, this
unequal towing could magnify differences in results.
Another analyst I’m working with “solved” this problem by randomly identifying
and eliminating 16 of the tows in which the control gear was on the port side
so the analysis was restricted to tows for which each gear was on each side 4
times (for the example above). This does not seem correct to me.
I’ve run randomization tests to test for side bias (and day/night bias) in the
catches of select species. There is a side bias (and sometimes a time of day
bias) in some cases. What is the best way to adjust for this bias so I can
determine whether the difference between the control and experimental gear
catches is due to the gear modification alone.
I hope this makes sense. Thanks so much for your time!
Laura M. Lee
Senior Stock Assessment Scientist
Division of Marine Fisheries
Department of Environmental Quality
252 808 8094<tel:(252)%20808-8094> office
252 726 6062<tel:(252)%20726-6062> fax
3441 Arendell Street
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Morehead City, NC 28557-0769
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