Modeling the Importance of Sample Size in Relation to Error in MHC-Based Mate-Choice Studies on Natural Populations

Understanding the genetic basis of mate choice in natural populations is a challenging undertaking. Mechanistic investigations of neural and genetic exemplars must be interpreted in the context of population-level effects, and complex demographic and ecological processes that may mask MHC-based mate-choice effects. This is particularly exacerbated in highly polymorphic MHC-based mate choice studies, which require a large sample size to sufficiently characterize an allele distribution in a population, and typically yield small effect sizes. A careful consideration of sample size, statistical power, and effect size is therefore critical for correctly interpreting conclusions in this field. To address these concerns, we used Monte Carlo randomization tests to investigate the effects of sample size on a simulated population of breeding organisms with intermediate MHC polymorphism. We illustrate the impact of sample size on error rates and effect sizes, and highlight the potential for incorrect conclusions in the existing literature.