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A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
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Medicina
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JoVE Journal Medicina
A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

DOI:
10.3791/53169-v

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10:46 min

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December 09, 2015

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, , ,
1Department of Neurology,Royal Melbourne Hospital, 2Department of Medicine (RMH),The University of Melbourne, 3Department of Neurology,Ulster Hospital, 4National Centre for Epidemiology and Population Health,Australian National University

Capítulos

  • 00:05Título
  • 01:06Preparing the Observed Relapse Onset Data
  • 03:10Building a Model
  • 04:40Estimating the Peak Relapse Probability
  • 05:26Modeling the Ultraviolet Radiation Data (UVR)
  • 07:05Modeling UVR-trough-to-relapse-peak Lag
  • 08:34Results: MS-patient Seasonal Relapse with an Equatorial Effect
  • 09:50Conclusion

Summary

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Combining plot analysis with trigonometric regression is a robust method for exploring complex, cyclical phenomena such as relapse onset timing in multiple sclerosis (MS). This method enabled unbiased characterisation of seasonal trends in relapse onset permitting novel inferences around the influence of seasonal variation, ultraviolet radiation (UVR) and latitude.

Tags

Seasonal VariationTrigonometric Regression ModelingMultiple SclerosisRelapse DataStataPlot AnalysisStatistical Regression ModelingSeasonal InfluenceLatitudinal InfluenceRelapse ProbabilityConfoundersBest-fit Convergence

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