A Statistical Method for Analyzing Data Collected by a Creel/Angler Survey (Part 2)

Abstract

This article describes a unique analytical method employed to characterize angler activities on the lower 6-mile stretch of the Passaic River in New Jersey. The method used data collected by a creel/angler survey that was designed to capture the information necessary to calculate the exposure factors needed to characterize the fish consumption pathway for recreational anglers in a human health risk assessment for the river. The survey used two methods to address the challenges of conducting a creel/angler survey in an urban and industrial setting with limited river access. While unique, the analytical method described in this article is based upon accepted methods of interpreting survey data and basic laws of probability. This article was written as a companion to two other articles, also in this issue and cited here, of which one describes in detail the survey methodology designed for the lower Passaic River creel/angler survey to meet various challenges unique to conducting such a survey in urban and industrialized rivers, and the other presents, validates, and interprets the results of the lower Passaic River work relating to human exposure factors using the methodology described in this article.

The authors thank the journal reviewers of this article for their attention to detail and thorough comments. The edits and comments received greatly improved this article.

The work and research underlying this paper was performed with financial support from Tierra Solutions, Inc.

Notes

∗The sample frame is the actual list of units from which the random sample can be drawn.

∗This assumption is consistent with the observations on the Passaic River, in that virtually all anglers fished at only one site. If individual anglers are observed to fish at several sites, it would be more appropriate to partition the months fished across locations as well as across weekday/weekend and morning/afternoon.

∗For some strata, the estimated number of fishing days may not be an integer. The hypergeometric distribution applies only to integers. This was addressed in the example by rounding the estimated number of fishing days to the nearest integer. The importance of this simplification can be addressed in a sensitivity analysis.

^†Event 1 = interviewed one or more times in the stratum; event 2 = not interviewed in the stratum.

∗H(0,2,4,20) = the probability of 0 successes in a sample of 2 without replacement from a population of 20 with 4 successes in the population.