Table 2.

Binary logistic regression of the presence or absence of each component of the target image in each participant's attempted image on the corresponding component in each of the five potential models. We control for non-independence between participant's image components using clustered robust standard errors. The odds ratios reported reveal a large and significant bias for the best model, but also biases for the three next best models. We control for generation, male and age (see the electronic supplementary material, table S4 for full regression model). Robust standard errors in parentheses.

predictor variables	coefficients as odds ratios (standard errors)
model 1	3.910*** (1.258)
model 2	2.481*** (0.867)
model 3	1.747* (0.557)
model 4	2.187*** (0.583)
model 5	0.893 (0.260)
pseudo-R2	0.283
n	810 (45 clusters)

*p < 0.1; **p < 0.05; ***p < 0.01.