How do I interpret the AIC?

Interpreting coefficients in GLMs

This is an archive of an external source. The original is here Date: November 11, 2016 Author: Gordana Popovic In linear models, the interpretation of model parameters is linear. For example, if a you were modelling plant height against altitude and your coefficient for altitude was -0.9, then plant height will decrease by 1.09 for every increase in altitude of 1 unit. For generalised linear models, the interpretation is not this straightforward.

Some Intuition Behind Hierarchical Modeling

This is an archive of an external source Date: November 13, 2017 Author: Kert Viele Hierarchical modeling is a powerful tool for making inferences about multiple groups in clinical trials, whether these groups are multiple indications or tumor types in an oncology study, multiple sites in a device clinical trial, or any other source of patient heterogeneity. Hierarchical models that share information across groups form a backbone of modern Bayesian thinking.