Low risk of COVID-19 transmission in GI endoscopy
Alessandro Repici, Giovanni Aragona, Gianpaolo Cengia, P. Cantù, Marco Spadaccini, Roberta Maselli, Silvia Carrara, Andrea Anderloni, Alessandro Fugazza, Fábio Pace, Thomas Rösch
Abstract
<h3>Abstract</h3> Fishing gear is constantly being improved to select certain sizes and species while excluding others. Experiments are conducted to quantify the selectivity and the resulting data needs to be analyzed using specialized statistical methods in many cases. Here, we present a new estimation tool for analyzing this type of data: an R package named selfisher. It can be used for both active and passive gears, and can handle different trial designs. It allows fitting models containing multiple fixed effects (e.g. length, total catch weight, mesh size, water turbidity) and random effects (e.g. haul). A bootstrapping procedure is provided to account for between and within haul variability and overdispersion. We demonstrate its use via four case studies including (1) covered codend analyses of four gears, (2) a paired gear study with numerous potential covariates, (3) a catch comparison study of unpaired hauls of gillnets and (4) a catch comparison study of paired hauls using polynomials and splines. This free and open source software will make it easier to model fishing gear selectivity, teach the statistical methods, and make analyses more repeatable.