Mating preference can be a driver of sexual selection and assortative mating and is, therefore, a key element in evolutionary dynamics. Positive mating preference by similarity is the tendency for the choosy individual to select a mate which possesses a similar variant of a trait. Such preference can be modelled using Gaussian-like mathematical functions that describe the strength of preference, but such functions cannot be applied to empirical data collected from the field. As a result, traditionally, mating preference is indirectly estimated by the degree of assortative mating (using Pearson's correlation coefficient, r) in wild captured mating pairs. Unfortunately, r and similar coefficients are often biased due to the fact that different variants of a given trait are nonrandomly distributed in the wild, and pooling of mating pairs from such heterogeneous samples may lead to “false–positive” results, termed “the scale-of-choice effect” (SCE). Here we provide two new estimators of mating preference (Crough and Cscaled) derived from Gaussian-like functions which can be applied to empirical data. Computer simulations demonstrated that r coefficient showed robust estimations properties of mating preference but it was severely affected by SCE, Crough showed reasonable estimation properties and it was little affected by SCE, while Cscaled showed the best properties at infinite sample sizes and it was not affected by SCE but failed at biological sample sizes. We recommend using Crough combined with the r coefficient to infer mating preference in future empirical studies.

The mode in which sexual organisms choose mates is a key evolutionary process, as it can have a profound impact on fitness and speciation. One way to study mate choice in the wild is by measuring trait correlation between mates. Positive assortative mating is inferred when individuals of a mating pair display traits that are more similar than those expected under random mating while negative assortative mating is the opposite. A recent review of 1134 trait correlations found that positive estimates of assortative mating were more frequent and larger in magnitude than negative estimates. Here we describe the scale-of-choice effect (SCE), which occurs when mate choice exists at a smaller scale than that of the investigator's sampling, while simultaneously the trait is heterogeneously distributed at the true scale-of-choice. We demonstrate the SCE by Monte Carlo simulations and estimate it in two organisms showing positive (Littorina saxatilis) and negative (L. fabalis) assortative mating. Our results show that both positive and negative estimates are biased by the SCE by different magnitudes, typically towards positive values. Therefore, the low frequency of negative assortative mating observed in the literature may be due to the SCE's impact on correlation estimates, which demands new experimental evaluation.