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.