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Hierarchical Bayesian models specify priors on parameters and hyperpriors on the parameters of the prior distributions

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Modelling strategies for analyzing an effect of a predictor through higher hierarchical level

Regarding the first point A model like this gives biased result due to unmeasured confounding (unavailable variables): e.g. very sick patients are excluded from rehabilitation and very fit patients d …
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