2009
DOI: 10.1016/j.fishres.2008.09.027
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A simple statistical method for catch comparison studies

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Cited by 106 publications
(103 citation statements)
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“…Paired t-tests were performed to judge whether the differences in catch amount for two codends were statistically significant. GLMM (Generalised Linear Mixed Models) was used to compare the length of obtained the veined rapa whelk and three by-catch species (Holst and Revill 2009). The proportion of the veined rapa whelk and three by-catch species retained at total length by 72 mm square-mesh codend (SMC) was calculated for each length as: P = SMC count at length ÷ (SMC and CD total count at length).…”
Section: Methodsmentioning
confidence: 99%
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“…Paired t-tests were performed to judge whether the differences in catch amount for two codends were statistically significant. GLMM (Generalised Linear Mixed Models) was used to compare the length of obtained the veined rapa whelk and three by-catch species (Holst and Revill 2009). The proportion of the veined rapa whelk and three by-catch species retained at total length by 72 mm square-mesh codend (SMC) was calculated for each length as: P = SMC count at length ÷ (SMC and CD total count at length).…”
Section: Methodsmentioning
confidence: 99%
“…The proportion of the veined rapa whelk and three by-catch species retained at total length by 72 mm square-mesh codend (SMC) was calculated for each length as: P = SMC count at length ÷ (SMC and CD total count at length). The polynomial regression GLMM (with random intercepts) was used to fit curves for the expected proportions of the total catch retained by the 72 mm square-mesh codend (Holst and Revill 2009). The glmmPQL function in MASS package of the R statistical software, which uses a penalized quasi-likelihood approach, was used to fit the GLMM model (Holst and Revill 2009).…”
Section: Methodsmentioning
confidence: 99%
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“…The proportion of catch at each length class for shrimp and major bycatch species from the control and experimental trawls was analyzed using the generalized linear mixed models (GLMM) with carapace length (shrimp) or fish length (bycatch) as the explanatory variable (fixed effect), the catch proportion as the response variable, the individual tow as the random effect, and subsample ratio as an offset, following the technique described in Holst and Revill (2009). The GLMM was implemented using the glmmPQL function in the MASS package (Venables and Ripley 2002) of R statistical software (R Core Team 2014), which used a penalized quasilikelihood approach (Breslow and Clayton 1993).…”
Section: Catch Sampling and Analysismentioning
confidence: 99%
“…The approach suggested by Holst and Revill (2009) was adopted for the current dataset where polynomial generalised linear mixed model (GLMM) analyses were performed using the R software package. The GLMM method uses low-order polynomial approximations (3rd-order, logit link, net type fixed term) to fit the proportions at length retained in the square codend relative to the total numbers retained by both square and diamond codends, and produces realistic curves and variance estimate bands.…”
Section: Statistical Analysesmentioning
confidence: 99%