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Sinusoidal Cox Regression—A Rare Cancer Example

dc.contributor.authorEfird, Jimmy T.
dc.date.accessioned2016-07-28T17:39:22Z
dc.date.available2016-07-28T17:39:22Z
dc.date.issued2010-11
dc.description.abstractEvidence of an association between survival time and date of birth would suggest an etiologic role for a seasonally variable environmental exposure occurring within a narrow perinatal time period. Risk factors that may exhibit seasonal epidemicity include diet, infectious agents, allergens, and antihistamine use. Typically data has been analyzed by simply categorizing births into months or seasons of the year and performing multiple pairwise comparisons. This paper presents a statistically robust alternative, based upon a trigonometric Cox regression model, to analyze the cyclic nature of birth dates related to patient survival. Disease birth-date results are presented using a sinusoidal plot with peak date(s) of relative risk and a single P value that indicates whether an overall statistically significant seasonal association is present. Advantages of this derivative-free method include ease of use, increased power to detect statistically significant associations, and the ability to avoid arbitrary, subjective demarcation of seasons.en_US
dc.identifier.citationCancer Informatics; 9: p. 265-279en_US
dc.identifier.doi10.4137/CIN.S6202
dc.identifier.issn1176-9351
dc.identifier.pmidpmc2998934en_US
dc.identifier.urihttp://hdl.handle.net/10342/5840
dc.relation.urihttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC2998934/en_US
dc.subjectsinusoidal Cox regressionen_US
dc.subjectseasonality of birthen_US
dc.titleSinusoidal Cox Regression—A Rare Cancer Exampleen_US
dc.typeArticleen_US
ecu.journal.nameCancer Informaticsen_US
ecu.journal.pages265-279en_US
ecu.journal.volume9en_US

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