Using repeatability to study physiological and behavioural traits: ignore time-related change at your peril

Broad sense repeatability, which refers to the extent to which individual differences in trait scores are maintained over time, is of increasing interest to researchers studying behavioural or physiological traits. Broad sense repeatability is most often inferred from the statistic R (the intraclass correlation, or narrow sense repeatability). However, R ignores change over time, despite the inherent longitudinal nature of the data (repeated measures over time). Here, we begin by showing that most studies ignore time-related change when estimating broad sense repeatability, and estimate R with low statistical power. Given this problem, we (1) outline how and why ignoring time-related change in scores (that occurs for whatever reason) can seriously affect estimates of the broad sense repeatability of behavioural or physiological traits, (2) discuss conditions in which various indices of R can or cannot provide reliable estimates of broad sense repeatability, and (3) provide suggestions for experimental designs for future studies. Finally, given that we already have abundant evidence that many labile traits are 'repeatable' in that broad sense (i.e. R > 0), we suggest a shift in focus towards obtaining robust estimates of the repeatability of behavioural and physiological traits. Given how labile these traits are, this will require greater experimental (and/or statistical) control and larger sample sizes in order to detect and quantify change over time (if present).