This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 138
Type: Contributed
Date/Time: Monday, August 2, 2010 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics and the Environment
Abstract - #309308
Title: Sample-Size Estimation for Detecting Trends in Repeated Surveys
Author(s): Mark C. Otto*+
Companies: U.S. Fish and Wildlife Service
Address: 2302 Lackawanna St, Adelphi, MD, 20783, United States
Keywords: survey design ; trend estimation

Detecting a linear trend is the parameter of interest for most repeated surveys. Where pilot study sampling variances may exist, but time series structure and process variance information is almost never available. We use a Kalman filter model with an observation equation describing sampling error as a function of sample size and first order difference model ith a trend on the log-transformed survey estimates to describe the time series process. We estimate annual sample sizes for over different number of years with varying process to sampling error ratios. Sample size is determined in two ways: analytically and by simulation to construct of sample size power curves. An example of the Western Gulf Coast Mottled Duck Survey and differences in the sample size estimation methods are discussed.

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