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Bayesian comparison of explicit and implicit causal inference strategies in multisensory heading perception

Fig 7

Sensitivity analysis of factorial model comparison.

Protected exceedance probability of distinct model components for each model factor in the joint fits. Each panel also shows the estimated posterior frequency (mean ± SD) of distinct model components, and the Bayesian omnibus risk (BOR). Each row represents a variant of the factorial comparison. 1st row: Main analysis (as per Fig 6A). 2nd row: Uses marginal likelihood as model comparison metric. 3rd row: Uses hyperprior α₀ = 1 for the frequencies over models in the population (instead of a flat prior over model factors). 4th row: Uses ‘probability matching’ strategy for the Bayesian causal inference model (replacing model averaging). 5th row: Includes probability matching as a sub-factor of the Bayesian causal inference family (in addition to model averaging).

doi: https://doi.org/10.1371/journal.pcbi.1006110.g007