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Assessing Seasonality Variation with Harmonic Regression: Accommodations for Sharp Peaks
The use of the harmonic regression model is well accepted in the epidemiological and biostatistical communities as a standard procedure to examine seasonal patterns in disease occurrence. While these models may provide good fit to periodic patterns with relatively symmetric rises and falls, for some...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7068504/ https://www.ncbi.nlm.nih.gov/pubmed/32085630 http://dx.doi.org/10.3390/ijerph17041318 |
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author | Ramanathan, Kavitha Thenmozhi, Mani George, Sebastian Anandan, Shalini Veeraraghavan, Balaji Naumova, Elena N. Jeyaseelan, Lakshmanan |
author_facet | Ramanathan, Kavitha Thenmozhi, Mani George, Sebastian Anandan, Shalini Veeraraghavan, Balaji Naumova, Elena N. Jeyaseelan, Lakshmanan |
author_sort | Ramanathan, Kavitha |
collection | PubMed |
description | The use of the harmonic regression model is well accepted in the epidemiological and biostatistical communities as a standard procedure to examine seasonal patterns in disease occurrence. While these models may provide good fit to periodic patterns with relatively symmetric rises and falls, for some diseases the incidence fluctuates in a more complex manner. We propose a two-step harmonic regression approach to improve the model fit for data exhibiting sharp seasonal peaks. To capture such specific behavior, we first build a basic model and estimate the seasonal peak. At the second step, we apply an extended model using sine and cosine transform functions. These newly proposed functions mimic a quadratic term in the harmonic regression models and thus allow us to better fit the seasonal spikes. We illustrate the proposed method using actual and simulated data and recommend the new approach to assess seasonality in a broad spectrum of diseases manifesting sharp seasonal peaks. |
format | Online Article Text |
id | pubmed-7068504 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-70685042020-03-19 Assessing Seasonality Variation with Harmonic Regression: Accommodations for Sharp Peaks Ramanathan, Kavitha Thenmozhi, Mani George, Sebastian Anandan, Shalini Veeraraghavan, Balaji Naumova, Elena N. Jeyaseelan, Lakshmanan Int J Environ Res Public Health Article The use of the harmonic regression model is well accepted in the epidemiological and biostatistical communities as a standard procedure to examine seasonal patterns in disease occurrence. While these models may provide good fit to periodic patterns with relatively symmetric rises and falls, for some diseases the incidence fluctuates in a more complex manner. We propose a two-step harmonic regression approach to improve the model fit for data exhibiting sharp seasonal peaks. To capture such specific behavior, we first build a basic model and estimate the seasonal peak. At the second step, we apply an extended model using sine and cosine transform functions. These newly proposed functions mimic a quadratic term in the harmonic regression models and thus allow us to better fit the seasonal spikes. We illustrate the proposed method using actual and simulated data and recommend the new approach to assess seasonality in a broad spectrum of diseases manifesting sharp seasonal peaks. MDPI 2020-02-18 2020-02 /pmc/articles/PMC7068504/ /pubmed/32085630 http://dx.doi.org/10.3390/ijerph17041318 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ramanathan, Kavitha Thenmozhi, Mani George, Sebastian Anandan, Shalini Veeraraghavan, Balaji Naumova, Elena N. Jeyaseelan, Lakshmanan Assessing Seasonality Variation with Harmonic Regression: Accommodations for Sharp Peaks |
title | Assessing Seasonality Variation with Harmonic Regression: Accommodations for Sharp Peaks |
title_full | Assessing Seasonality Variation with Harmonic Regression: Accommodations for Sharp Peaks |
title_fullStr | Assessing Seasonality Variation with Harmonic Regression: Accommodations for Sharp Peaks |
title_full_unstemmed | Assessing Seasonality Variation with Harmonic Regression: Accommodations for Sharp Peaks |
title_short | Assessing Seasonality Variation with Harmonic Regression: Accommodations for Sharp Peaks |
title_sort | assessing seasonality variation with harmonic regression: accommodations for sharp peaks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7068504/ https://www.ncbi.nlm.nih.gov/pubmed/32085630 http://dx.doi.org/10.3390/ijerph17041318 |
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