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Impact models: Bayesian regressions

The best in impact models
We use Bayesian regressions because they have several advantages over classic methods: they deliver stable, across-time results, avoid overestimating the impact strength and provide better results for multicolinearity. This comes from the fact that previous knowledge of the investigated associations can be integrated into the model. This makes Bayesian regressions ideal not only for ad-hoc impact models but especially for tracking studies.