Design and analysis of multiple-choice feeding-preference experiments

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Preferential Feeding: An Optimization Strategy in Sea Urchins

Robert Vadas (1977)

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Analysis of feeding preference experiments.

Leo P. Renaud, Eric C. Peterson (1989)

Published studies of consumer feeding preferences using foods that experience autogenic change in mass, numbers, area, etc., on the time scale of a feeding trial fail to employ appropriate statistical analyses to incorporate controls for those food changes occurring in the absence of the consumer. The studies that run controls typically use them to calculate a constant "correction factor", which is subtracted prior to formal data analysis. This procedure constitutes a non-rigorous suppression of variance that overstates the statistical significance of observed differences. The appropriate statistical analysis for preference tests with two foods is usually a simple t-test performed on the between-food differences in loss of mass (or numbers, area, etc.) comparing the results of experimentals with consumers to controls without consumers. Application of this recommended test procedure to an actual data set illustrates how low replication in controls, which is typical of most studies of feeding preference, inhibits detection of an apparently large influence of previous mechanical damage (simulated grazing) in reducing the attractiveness of a brown alga to a sea urchin.