- N in dataset: 3247 - excluded 73 with incomplete data (left 3174) - excluded 428 with < 15 trials after RT exclusion (left 2746) # Results Bayesian mixed-effects models: No "significant" effects of condition (maybe slightly smaller mean drift rate?). - `parameter ~ condition + (1 + condition | study)` - condition coded $[-0.5, 0.5]$ ```r # condition effects boundary: b = 0.09, [−0.30, 0.44], BF = 0.32 weight on accuracy: b = 0.07 [−0.19, 0.32], BF = 0.36 mean drift rate: b = −0.11 [−0.34, 0.13], BF = 0.81 # frequentist mixed model: b = −0.12, SE = 0.04, t(28) = −2.75, p = .010 non-decision time: b = 0.07 [−0.33, 0.49], BF = 0.24 starting-point: b = −0.004 [−0.11, 0.11], BF = 0.2 ``` ![[param__posteriors 2.png|1400]] ![[param__posteriors_study 1.png|1400]] ![[parameters_all.png|800]] # Correlations between parameters and behavior `supplement__pause.Rmd` People with larger weight on accuracy are more discerning news sharers. ![[Pasted image 20220222001326.png]] People with larger boundaries are **less** discerning?! Probably because of outliers. See figure below ![[Pasted image 20220222001422.png]] After removing outliers (boundary > 5), small positive effect of boundary on discernment. ![[Pasted image 20220222002144.png]] Exclude even more outliers (boundary > 3). ![[Pasted image 20220222002339.png]]