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Activity Number: 550 - Statistics on Street Corners
Type: Invited
Date/Time: Wednesday, July 31, 2019 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Graphics
Abstract #300461 Presentation
Title: Visual Inference for Model Checking
Author(s): Adam Loy* and Heike Hofmann and Dianne Cook
Companies: Carleton College and Iowa State University and Monash University
Keywords: Model diagnostics; Statistical education; Multilevel models; Lineup protocol

We strive to specify models that resemble data collected in studies or observed from processes. One way to check whether the model is a reasonable abstraction of reality is to display the data in the model space, such as residual plots for linear models. While these plots are well-behaved for simple models, such as linear regression with uncorrelated errors, this is not the case for more-complex models. For example, residual plots for multilevel models often show patterns that are artifacts of the model-fitting process, and are not indicative of a model deficiency. This talk will outline how visual inference can be utilized during model validation for multilevel models, and how this approach can be generalized to other models. I will also discuss how these techniques have informed how I teach model validation to undergraduate students.

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

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