February 15-18, 2009 Washington State Convention Center Seattle ...

MULTIPLE COMPARISONS OF MEANS VS. REGRESSION ANALYSIS IN AQUACULTURE
RESEARCH
Steeve Pomerleau
Aquaculture/Fisheries Center
University of Arkansas at Pine Bluff
Mail Slot 4912
1200 North University Drive
Pine Bluff, AR 71601 USA
spomerleau@uaex.edu
Comparing treatment means by testing for statistical significant differences is probably the most common approach used in
aquaculture research. However, in several common types of aquaculture experiments such as in fertilization experiments or
stocking density experiments, where treatments correspond to several levels of a quantitative or continuous variable, comparing
treatment means for significant differences is not an appropriate and efficient way of analyzing the data and of obtaining
meaningful information. In those types of experiments, regression analysis should be used to estimate and identify trends or
relationship instead of simply comparing means to find which treatment gave the best results. Unfortunately, in the literature,
multiple comparisons of treatment means are too often unwarranted and the regression analysis is too often ignored where it
would have been the most appropriate approach for the factors being studied. Comparing treatment means is not necessarily
wrong; it is just that more valuable information could sometime be attained with the same amount of resources if a regression
analysis and a slightly different experimental design were used.
This problem has been raised several times in the literature. Chew (1976) wrote: “Duncan’s multiple range test (MRT) is very
often inappropriately used to compare treatments that are factorial in nature or that correspond to several levels of a quantitative
or continuous variable.” Lowry (1992) wrote: “Pairwise, multiple comparisons are appropriate only for comparing unstructured,
qualitative treatments.” Dawkins (1983) wrote: “How do we persuade biologists of the futility of significance testing
between mean responses (ordinate value of y), at series of dose-rates (abscissa values of x), along response curves?” Knud-
Hansen (1997) wrote: “Although the statistical community is quite clear on this point, the aquaculture community (among
other scientific disciplines) has yet to appreciate the inappropriateness and gross inefficiency of multiple range test usage in
analyzing structured experiments.”
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