Negative Associations Between Early and Adult Performance Arise from Colider Selection Bias

Negative Associations Between Early and Adult Performance Arise from Colider Selection Bias Michel Nivard Güllich et al. argue that among elite performers there is a negative association between early and adult performance, a pattern they link to distinct developmental causal mechanisms for early, and adult elite performance. Using simple simulations, we show that this pattern arises naturally from collider bias when selection into elite samples depends on both early and adult performance. Consequently, associations estimated within elite samples are descriptively accurate for the selected population, but causally misleading, and should not be used to infer developmental mechanisms of elite performance without explicit modeling of the selection process. Güllich et al.(Güllich et al. 2025) recently review the causal mechanisms by which the most exceptional (academic, athletic, professional) talent arises. Based on their reading of the literature, they conclude that: “Across the highest adult performance levels, peak performance is negatively correlated with early performance.” This observation is likely entirely explained by collider bias, also known as Berkson’s paradox, a well-known but frequently misunderstood bias in epidemiology and the social sciences(Griffith et al. 2020; Holmberg and Andersen 2022; Cole et al. 2009; Munafò et al. 2017). If selection into a sample (here: elite performers) is caused by both the exposure (early performance) and the outcome (adult performance), conditioning on that selection induces a spurious negative association, even when early performance and adult performance are highly positively correlated in the population. We simulate a data-generating process in which early and adult performance share a common latent cause (i.e. talents, training, opportunities, social and psychological support) and 1 both early and adult erformance contribute to selection into an elite group of athletes use for analysis. −5.0 −2.5 0.0 2.5 5.0 −2.5 0.0 2.5 5.0 Early performance Adult performance Figure 1: Relationship between early and adult performance in the full population (black) and elite performers (red). Conditioning on elite status induces a negative association despite a positive population relationship. It becomes clear from Figure 1 that although early and adult performance are positively related in the population, conditioning on elite status reverses the association. The negative slope among elite performers is therefore not evidence against a causal role of early performance; it is the mechanical consequence of selection. The implications extend beyond bivariate associations. Whenw e further five causal variables contribute equally to early and adult performance the bias persists to the effects of these variables on performance in the selected sample. In the full population, the effects are recovered accurately. In the selected (elite) sample, however, estimation is strongly attenuated, and severely biased and may even suggest opposite effects on early versus adult performance. Given the risk of bias the analysis Güllich et al.(Güllich et al. 2025) perform to elucidate the (seemingly distinct) causes of early and late elite performance cannot be interpreted mechanistically. The analysis requires a formal model that fully accounts for selection. 2 Table 1: True and estimated covariate effects in the presence of simulated collider bias in the full and selected samples Whole sample Selected sample Early Adult Early Adult Covariate True � SE � SE � SE � SE X1 0.3 0.300 0.005 0.297 0.005 0.092 0.028 0.044 0.027 X2 0.3 0.290 0.005 0.295 0.005 -0.013 0.028 0.032 0.027 X3 0.3 0.297 0.005 0.301 0.005 0.075 0.031 -0.006 0.029 X4 0.3 0.299 0.005 0.293 0.005 0.055 0.031 0.039 0.029 X5 0.3 0.299 0.005 0.300 0.005 0.000 0.029 0.047 0.028 Results of the multivariate simulation are presented in Table 1, these clearly reveal that while estimates in the full population are unbiased, conditioning on elite status produces attenuated, unstable, and even sign-reversed estimates of the effects of causes of performance. This is not a failure of measurement or modeling, but a direct consequence of selection on a collider. Negative associations between early and adult performance among elite performers are descriptively correct but causally uninformative. Interpreting such patterns as evidence for distinct developmental processes for early and adult skill acquisition is therefore unwarranted. Any attempt to infer causal mechanisms within selected elite samples must explicitly model the selection process—or risk mistaking bias for insight. References Cole, Stephen R, Robert W Platt, Enrique F Schisterman, Haitao Chu, Daniel Westreich, David Richardson, and Charles Poole. 2009. “Illustrating Bias Due to Conditioning on a Collider.” International Journal of Epidemiology 39 (2): 417–20. https://doi.org/10.1093/ ije/dyp334. Griffith, Gareth J., Tim T. Morris, Matthew J. Tudball, Annie Herbert, Giulia Mancano, Lindsey Pike, Gemma C. Sharp, et al. 2020. “Collider Bias Undermines Our Understanding of COVID-19 Disease Risk and Severity.” Nature Communications 11 (1). https://doi.org/ 10.1038/s41467-020-19478-2. Güllich, Arne, Michael Barth, David Z. Hambrick, and Brooke N. Macnamara. 2025. “Recent Discoveries on the Acquisition of the Highest Levels of Human Performance.” Science 390 (6779). https://doi.org/10.1126/science.adt7790. Holmberg, Mathias J., and Lars W. Andersen. 2022. “Collider Bias.” JAMA 327 (13): 1282. https://doi.org/10.1001/jama.2022.1820. 3 Munafò, Marcus R, Kate Tilling, Amy E Taylor, David M Evans, and George Davey Smith. 2017. “Collider Scope: When Selection Bias Can Substantially Influence Observed Associations.” International Journal of Epidemiology 47 (1): 226–35. https://doi.org/10.1093/ ije/dyx206. 4