We often know more than we think: Using prior knowledge to avoid prior problems #BayesInPsych

One of the unique features of Bayesian statistical and computational modelling is the prior distribution. A prior distribution is both conceptually and formally necessary to do any sort of Bayesian modelling. If we are estimating the values of model parameters (e.g., regression coefficients), we do this by updating our prior beliefs about the parameter values […]

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