The effect of sample size on estimates of covariation
While the sample sizes presented in this study are modest, they are within the ranges suggested as sufficient in the literature. For example, Cheverud’s analysis (1988) suggests that 40 individuals is a large enough sample size for estimating genetic variance from phenotypic variance. More recent simulation-based studies suggest that adequate sample sizes likely vary depending on the statistics being used and the properties of one’s dataset, but show that samples sizes of 16-32 are large enough to accurately estimate most common statistics associated with variance-covariance datasets (Grabowski and Porto 2017; Watanabe 2022). There are also several previously published empirical studies examining the properties of variation-covariation with samples sizes similar to our own (Polly 2005; Goswami and Polly 2010; Blankers et al. 2015). To further ensure that our sample size was adequate for detecting differences in means between groups we performed power analyses to calculate the minimum sample size required across a range of correlations and effect sizes with 80% power. We also performed Monte Carlo simulations across a range of hypothetical trait values and standard deviations to determine at which sample sizes estimates of variation stabilized. Full methodologies and results can be found in the appendix B, but overall, we found that our samples sizes were sufficient for detecting differences between groups even at small effect sizes (η2 >0.02) and that estimates of trait variation stabilized at 20 individuals.