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Activity Number: 22 - Testing and Evaluation of High-Dimensional Models
Type: Topic Contributed
Date/Time: Sunday, July 28, 2019 : 2:00 PM to 3:50 PM
Sponsor: Section on Bayesian Statistical Science
Abstract #306846
Title: Inconvenient Diagnostics and Corrections for Convenience Samples
Author(s): Eloise Kaizar*
Companies: Ohio State University
Keywords: Genearlizability; Experiment; Observational Study

We often rely on convenience samples and otherwise incompletely collected experimental data. This raises questions about the relevance of the sample to 'real world' populations. The extent of selection bias and correctness of our models and other assumptions impact the quality of our statistical conclusions. Flexible models and relevant diagnostic procedures that take advantage of multiple data sources can improve inferential reliability.

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

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