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Appendices239ASupplementary Table 9 - Model table for the Bayesian mixed model that predicts RT from Pre-date attractiveness ratings and Gender. This analysis was performed on the complete cases-dataset.PredictorsRTEstimates CI (95%)Intercept 1.19 -0.93 – 3.34Gender[Female] 0.74 -1.49 – 2.92AttractivenessDistractor 2.06 0.61 – 3.48AttractivenessProbe -1.11 -2.83 – 0.65Gender[Female]: AttractivenessDistractor -0.10 -1.52 – 1.28Gender[Female]: AttractivenessProbe 2.06 0.28 – 3.79Random Effectsσ2 2580.38τ00 Subject 2.29τ11 Subject:AttractivenessDistractor 5.24τ11 Subject:AttractivenessProbe 19.83N Subject 55Observations 3198Notes: Gender was sum-coded, while Pre-date attractiveness ratings were centered around 4 (the middle option).Supplementary Table 10 - Model table for the Bayesian mixed model that predicts RT from Post-date attractiveness ratings and Gender. This analysis was performed on the complete cases-dataset.PredictorsRTEstimates CI (95%)Intercept 0.38 -1.38 – 2.19Gender[Female] -0.27 -2.19 – 1.63AttractivenessDistractor 1.78 0.55 – 3.01AttractivenessProbe -0.91 -2.48 – 0.64Gender[Female]: AttractivenessDistractor 0.46 -0.77 – 1.68Gender[Female]: AttractivenessProbe 1.19 -0.38 – 2.75Random Effectsσ2 2581.06τ00 Subject 1.30τ11 Subject:AttractivenessDistractor 1.73τ11 Subject:AttractivenessProbe 13.89N Subject 55Observations 3198Notes: Gender was sum-coded, while Post-date attractiveness ratings were centered around 4 (the middle option).Tom Roth.indd 239 08-01-2024 10:42