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R. C. Anderson-Sprecher

Publications and source records attributed to R. C. Anderson-Sprecher.

2 recordsLinked to original sources

A new method to compute standard-weight equations that reduces length-related bias

We propose a new method for developing standard-weight (Ws) equations for use in the computation of relative weight (Wr) because the regression line-percentile (RLP) method often leads to length-related biases in Ws equations. We studied the structural properties of W s equations developed by the RLP method through simulations, identified reasons for biases, and compared Ws equations computed by the RLP method and the new method. The new method is similar to the RLP method but is based on means of measured weights rather than on means of weights predicted from regression models. The new method also models curvilinear W s relationships not accounted for by the RLP method. For some length-classes in some species, the relative weights computed from Ws equations developed by the new method were more than 20 Wr units different from those using Ws equations developed by the RLP method. We recommend assessment of published Ws equations developed by the RLP method for length-related bias and use of the new method for computing new Ws equations when bias is identified. ?? Copyright by the American Fisheries Society 2005.

North American Journal of Fisheries Management↗

An alternative approach to detection of length-related biases in standard weight equations

We propose a new method for assessing length-related biases in standard weight (Ws) equations computed by the regression-line-percentile method. We evaluated the performance of the new method relative to two previous methods for assessing length-related biases using 15 data sets from which W s equations have been computed. The new method detected potentially serious length-related biases in 10 Ws equations, whereas one of the previously used methods failed to detect any biologically significant biases and the other method detected biases in only one equation. The new method can detect curvilinear relationships between Ws and length, so it provides insight that is not available from previous methods.

North American Journal of Fisheries Management↗