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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Smaller p-values and shorter confidence intervals via information sharing
Mixed effects models are used routinely in the biological and social sciences to share information across groups and to account for data dependence. The statistical properties of procedures derived from these models are often quite good on average across groups, but may be poor for any specific group. For example, commonly-used confidence interval procedures may maintain a target coverage rate on average across groups, but have near zero coverage rate for a group that differs substantially from the others. In this talk we discuss new confidence interval and p-value procedures that maintain group-specific frequentist guarantees, while still sharing information across groups to improve precision and power.
Peter Hoff is Professor of Statistical Science at Duke University. His current research interests include multivariate statistics and hierarchical modeling. He is a Fellow of the ASA and IMS, and is the author of “A First Course in Bayesian Statistical Methods”.
