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Full-Text Articles in Longitudinal Data Analysis and Time Series

Dynapenic Obesity And The Effect On Long-Term Physical Function And Quality Of Life: Data From The Osteoarthritis Initiative, John A. Batsis, Alicia J. Zbehlik, Dawna Pidgeon, Stephen J. Bartels Oct 2015

Dynapenic Obesity And The Effect On Long-Term Physical Function And Quality Of Life: Data From The Osteoarthritis Initiative, John A. Batsis, Alicia J. Zbehlik, Dawna Pidgeon, Stephen J. Bartels

Dartmouth Scholarship

Obesity is associated with functional impairment, institutionalization, and increased mortality risk in elders. Dynapenia is defined as reduced muscle strength and is a known independent predictor of adverse events and disability. The synergy between dynapenia and obesity leads to worse outcomes than either independently. We identified the impact of dynapenic obesity in a cohort at risk for and with knee osteoarthritis on function.


Case Studies In Evaluating Time Series Prediction Models Using The Relative Mean Absolute Error, Nicholas G. Reich, Justin Lessler, Krzysztof Sakrejda, Stephen A. Lauer, Sopon Iamsirithaworn, Derek A T Cummings Dec 2014

Case Studies In Evaluating Time Series Prediction Models Using The Relative Mean Absolute Error, Nicholas G. Reich, Justin Lessler, Krzysztof Sakrejda, Stephen A. Lauer, Sopon Iamsirithaworn, Derek A T Cummings

Nicholas G Reich

Statistical prediction models inform decision-making processes in many real-world settings. Prior to using predictions in practice, one must rigorously test and validate candidate models to ensure that the proposed predictions have sufficient accuracy to be used in practice. In this paper, we present a framework for evaluating time series predictions that emphasizes computational simplicity and an intuitive interpretation using the relative mean absolute error metric. For a single time series, this metric enables comparisons of candidate model predictions against naive reference models, a method that can provide useful and standardized performance benchmarks. Additionally, in applications with multiple time series, this …