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Comparisons of treatment means when factors do not interact in two-factorial studies
Authors:Jiawei Wei  Raymond J. Carroll  Kathryn K. Harden  Guoyao Wu
Affiliation:(1) Department of Statistics, Texas A&M University, 3143 TAMU, College Station, TX 77843, USA;(2) American Society of Nutrition, 9650 Rockville Pike, Bethesda, MD 20814-3990, USA;(3) Department of Animal Science, Faculty of Nutrition, Texas A&M University, 2471 TAMU, College Station, TX 77843, USA;
Abstract:Scientists in the fields of nutrition and other biological sciences often design factorial studies to test the hypotheses of interest and importance. In the case of two-factorial studies, it is widely recognized that the analysis of factor effects is generally based on treatment means when the interaction of the factors is statistically significant, and involves multiple comparisons of treatment means. However, when the two factors do not interact, a common understanding among biologists is that comparisons among treatment means cannot or should not be made. Here, we bring this misconception into the attention of researchers. Additionally, we indicate what kind of comparisons among the treatment means can be performed when there is a nonsignificant interaction among two factors. Such information should be useful in analyzing the experimental data and drawing meaningful conclusions.
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