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Abstract
Cluster sampling is a common survey design used pervasively in fisheries research to sample fish populations, but it is not widely recognized by researchers. Because fish collected via cluster sampling are not independent of each other, standard simple random sampling estimators and statistical tests that assume independence cannot be used to make inferences about fish populations. If the clustered nature of fisheries data is ignored, the main consequence is that the type I error rate of common statistical tests will be severely inflated and significant differences will often be found in group comparisons where none exist. The goal of this paper is to provide an introduction to the estimation of population attributes and analysis of fisheries data collected via cluster sampling. This article addresses the nature of clustered fisheries data, reviews the random cluster sampling estimators of population attributes, explores the implications of violating the assumption of independence in hypothesis testing, and reviews current statistical approaches that can be used to analyze appropriately clustered data.
Received November 8, 2013; accepted February 27, 2014
ACKNOWLEDGMENTS
Funding for this study was provided by the U.S. Fish and Wildlife Service Sportfish Restoration Program Grant F-57-R. I thank Jon Volstad and Michael Pennington for their aid with the MSE simulations. Paul Kostovick of the National Marine Fisheries Service provided the original survey data used in Pennington and Volstad's paper to test the MSE simulations. Thanks go to Jeremy King of the Massachusetts Division of Marine Fisheries, Kurt Gottschall of Connecticut Department of Environmental Protection, Linda Barry of the New Jersey Division of Fish and Wildlife, Jason Rock of the North Carolina Division of Marine Fisheries, and Deborah Leffler of the Florida Fish and Wildlife Conservation Commission for providing survey data. The analyses and conclusions drawn using the survey data are those of the author and do not necessarily represent the views of contributing agencies. Thanks to Chris Legault of the National Marine Fisheries Service, Mike Bednarski of the Massachusetts Division of Marine Fisheries, and two anonymous reviewers for comments that helped improve the quality of the manuscript. This is Massachusetts Division of Marine Fisheries Contribution Number 44.