Insensitivity of the analysis of variance to heredity-environment interaction.

UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
Douglas Wahlsten, Visiting Professor (Creator)
The University of North Carolina at Greensboro (UNCG )
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Abstract: It makes sense to attribute a definite percentage of variation in some measure of behavior to variation in heredity only if the effects of heredity and environment are truly additive. Additivity is often tested by examining the interaction effect in a two-way analysis of variance (ANOVA) or its equivalent multiple regression model. If this effect is not statistically significant at the a = 0.05 level, it is common practice in certain fields (e.g., human behavior genetics) to conclude that the two factors really are additive and then to use linear models, which assume additivity. Comparing several simple models of nonadditive, interactive relationships between heredity and environment, however, reveals that ANOVA often fails to detect nonadditivity because it has mueh less power in tests of interaction than in tests of main effects. Likewise, the sample sizes needed to detect real interactions are substantially greater than those needed to detect main effects. Data transformations that reduce interaction effects also change drastically the properties of the causal model and may conceal theoretically interesting and practically useful relationships. Ifthe goal of partitioning variance among mutually exclusive causes and calculating "heritability" coefficients is abandoned, interactive relationships can be examined more seriously and can enhance our understanding of the ways living things develop.

Additional Information

Behavioral and Brain Sciences 13, 109-120
Language: English
Date: 1990
Causal models, Gene action, Heritability, Nature/nurture, Power, Sample size, Scale transformation

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