Journal Article

Optimizing a stratified sampling design when faced with multiple objectives

Timothy J. Miller, John R. Skalski and James N. Ianelli

in ICES Journal of Marine Science

Published on behalf of ICES/CIEM

Volume 64, issue 1, pages 97-109
Published in print January 2007 | ISSN: 1054-3139
Published online November 2006 | e-ISSN: 1095-9289 | DOI: http://dx.doi.org/10.1093/icesjms/fsl013
Optimizing a stratified sampling design when faced with multiple objectives

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Miller, T. J., Skalski, J. R., and Ianelli, J. N. 2007. Optimizing a stratifield sampling design when faced with multiple objectives – ICES Journal of Marine Science, 64, 97–109.

For many stratified sampling designs, the data collected are used by multiple parties with different estimation objectives. Quantitative methods to determine allocation of sampling effort to different strata to satisfy the often disparate estimation objectives are lacking. Analytical results for the sampling fractions and sample sizes for primary units within each stratum of a stratified (multi-stage) sampling design that are optimal with respect to a weighted sum of relative variances for the estimation objectives are presented. Further, an approach for assessing gains or losses for each estimation objective by changing allocation of sample sizes to each stratum is provided. As an illustration, the analytical results are applied to determine optimal observer sampling fractions (coverage rates) for the North Pacific Groundfish Observer Programme (NPGOP), for which the multiple objectives are assumed to be bycatch (seabird, marine mammal, and non-targeted fish species) and total catch, and catch-at-length and -age of targeted fish species. Simultaneously optimizing a criterion that defines the strata of the NPGOP sampling design is also considered. When observer coverage rates are allowed to be gear-specific for the NPGOP design, the optimized objective function is between 10% and 28% less than the value corresponding to current sampling for annual data (2000–2003) and 12% less when optimized over all years combined.

Keywords: multi-parameter; North Pacific; observer coverage; optimal sampling; stratified sampling

Journal Article.  8119 words.  Illustrated.

Subjects: Environmental Science ; Marine and Estuarine Biology

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