# Robustness against conflicting prior information in regression

@inproceedings{Gagnon2021RobustnessAC, title={Robustness against conflicting prior information in regression}, author={Philippe Gagnon}, year={2021} }

Including prior information about model parameters is a fundamental step of any Bayesian statistical analysis. It is viewed positively by some as it allows, among others, to quantitatively incorporate expert opinion about model parameters. It is viewed negatively by others because it sets the stage for subjectivity in statistical analysis. Certainly, it creates problems when the inference is skewed due to a conflict with the data collected. According to the theory of conflict resolution (O…

## One Citation

Detecting and diagnosing prior and likelihood sensitivity with power-scaling

- Computer Science
- 2021

A diagnostic that can indicate the presence of prior-data conﬂict or likelihood noninformativity is suggested and limitations to the power-scaling approach are discussed.

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