The coefficient of cyclic variation: a novel statistic to measure the magnitude of cyclic variation

Emerging Themes in Epidemiology

Anthony JC Fulford¹ 

[1] MRC Keneba, MRC Unit, P.O. Box 273, Banjul, The Gambia

关键词: Cosinor analysis;    Coefficient of circular variation;    Truncated fourier series;    Circular data;    Periodic regression;   

Others  :  1092974
DOI  :  10.1186/1742-7622-11-15

 received in 2014-04-28, accepted in 2014-09-09,  发布年份 2014

【 摘 要 】

Background

Periodic or cyclic data of known periodicity are frequently encountered in epidemiological and biomedical research: for instance, seasonality provides a useful experiment of nature while diurnal rhythms play an important role in endocrine secretion. There is, however, little consensus on how to analysis these data and less still on how to measure association or effect size for the often complex patterns seen.

Results

A simple statistic, readily derived from Fourier regression models, provides a readily-understood measure cyclic variation in a wide variety of situations.

Conclusion

The coefficient of cyclic variation or similar statistics derived from the variance of a Fourier series could provide a universal means of summarising the magnitude of periodic variation.

【 授权许可】

   
2014 Fulford; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

【 参考文献 】

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