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Activity Number: 216 - Modern Bayesian Computing in Ecology
Type: Invited
Date/Time: Monday, July 30, 2018 : 2:00 PM to 3:50 PM
Sponsor: ENAR
Abstract #326874 Presentation
Title: Not All Hierarchical Models Are Created Equal: Interpretation, Model Adequacy and Statistical Computation
Author(s): Matthew Schofield* and Richard Barker
Companies: University of Otago and University of Otago
Keywords: Hierarchical models; Partial pooling; Latent variables; Model adequacy

Hierarchical models are widely used in the ecology. They have grown in popularity in connection with the advancement of MCMC and other developments in statistical computation. Unfortunately, our ability to specify and fit hierarchical models has not been matched by the capability to check the assumptions of the models, particularly as the hierarchical structure deepens. This is important because not all hierarchical models are created equal. On one hand, hierarchical modeling can allow for partial pooling and regularization. On the other, we can consider models with many more latent variables than we have data points and there is often a temptation to model ourselves out of any situation. In this talk, we will use several examples to consider which aspects of a hierarchical model are robust and well supported by the data, as well as which variables are likely to be dependent on assumptions and sensitive to model specification. This has implications for how we interpret model output and distinguish between different hierarchical specifications. We will discuss the interaction between model fitting, statistical computation and model specification.

Authors who are presenting talks have a * after their name.

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