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Activity Number:
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372
- SPEED: SPAAC SESSION IV
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Type:
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Topic-Contributed
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Date/Time:
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Thursday, August 12, 2021 : 12:00 PM to 1:50 PM
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Sponsor:
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Section on Statistical Learning and Data Science
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Abstract #318090
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Title:
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CosinoRmixedeffects: An R Package for Mixed-Effects Cosinor Models
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Author(s):
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Ruixue Hou* and Lewis E Tomalin and Mayte Suárez-Fariñas
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Companies:
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Icahn School of Medicine at Mount Sinai and Icahn School of Medicine at Mount Sinai and Icahn School of Medicine at Mount Sinai
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Keywords:
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Wearable data analysis;
cosinor;
mixed effects;
circadian data;
R
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Abstract:
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We introduce the cosinoRmixedeffects R package for modelling longitudinal periodic data using mixed-effects cosinor models. The model allows for covariates and interactions with the non-linear parameters MESOR, amplitude and acrophase. To facilitate ease of use, the package utilizes the syntax and functions of the widely used emmeans package, to obtain estimated marginal means and contrasts. Estimation and hypothesis testing involving the non-linear circadian parameters are carried out using bootstrapping. We illustrate the functionality of the package by modelling daily measurements of heart rate variability (HRV) collected among health care workers over several months. Differences in circadian patterns between genders, BMI and following infection with SARS-Cov-2 are evaluated.
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Authors who are presenting talks have a * after their name.
