Use of simulation-extrapolation estimation in catch-effort analyses

All catch-effort estimation methods implicitly assume catch and effort are known quantities, whereas in many cases, they have been estimated and are s ubject to error. We evaluate the application of a simulation-based estimati on procedure for measurement error models (J.R. Cook and L.A. Stefanski. 19 94. J. Am. Stat. Assoc. 89: 1314-1328) in catch-effort studies. The techniq ue involves a simulation component and an extrapolation step, hence the nam e SIMEX estimation. We describe SIMEX estimation in general terms and illus trate its use with applications to real and simulated catch and effort data . Correcting for measurement error with SIMEX estimation resulted in popula tion size and catchability coefficient estimates that were substantially le ss than naive estimates, which ignored measurement errors in some cases. In a simulation of the procedure, we compared estimators from SIMEX with "nai ve" estimators that ignore measurement errors in catch and effort to determ ine the ability of SIMEX to produce bias-corrected estimates. The SIMEX est imators were less biased than the naive estimators but in some cases were a lso more variable. Despite the bias reduction, the SIMEX estimator had a la rger mean squared error than the naive estimator for one of two artificial populations studied. However, our results suggest the SIMEX estimator may o utperform the naive estimator in terms of bias and precision for larger pop ulations.