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Activity Number: 449
Type: Contributed
Date/Time: Tuesday, August 11, 2015 : 2:00 PM to 2:45 PM
Sponsor: Biopharmaceutical Section
Abstract #317822
Title: Model Identification in Linear Fixed Effects Models
Author(s): Ondrej Blaha* and Julia Volaufova and Lynn Roy LaMotte
Companies: LSU Health Sciences Center and LSU Health Sciences Center and LSU Health Sciences Center
Keywords: Variable selection ; Model identification ; Information criteria ; True model
Abstract:

Our study focuses on numerical investigation of performances of current existing variable selection techniques incorporating statistics like adjusted R^2, AIC, BIC, or SBC for linear models. Specifically, we focus on the ability of these statistics to detect a true model among all possible sub-models. Furthermore, we explore the dependence of the successful true model detection on the parameter setting. Simulation studies were designed to investigate properties of detection of the true model among all possible models. Results provide a new perspective on the current, commonly used techniques. The consequences of the results are discussed as well.


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

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