Abstract
Abstract This paper presents results from simulations investigating the effect of sample size, number of within-subject repeats and relative degree of measurement error on the power and accuracy of test for fluctuating asymmetry (FA). These data confirm that sampling variation of population-level FA-estimates is large and that high sample size is required to obtain reasonably high power when testing for FA or comparing FA levels between populations. The results also clearly show that increasing the number of within-subject repeats can dramatically increase accuracy and power when measurement error is relatively high.
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