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Insensitivity of the analysis of variance to heredity-environment interaction

Published online by Cambridge University Press:  19 May 2011

Douglas Wahlsten
Douglas Wahlsten
Affiliation:
Department of Psychology, University of Alberta, Edmonton, Alberta, Canada T6G2E9, Electronic mail: userdlwa@ualtamts.bitnet
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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 α = 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 much 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 ofthe causal model and may conceal theoretically interesting and practically useful relationships. If the goal ofpartitioning 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.

Keywords

causal modelsgene actionheritabilitynature/nurturepowersample sizescale transformation
Type
Target Article
Information
Behavioral and Brain Sciences , Volume 13 , Issue 1 , March 1990 , pp. 109 - 120
Copyright
Copyright © Cambridge University Press 1990

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