Studying seasonality by using sine and cosine functions in regression analysis

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Abstract
STUDY OBJECTIVE: A statistical test that allows for adjustment of confounding can be helpful for the study of seasonal patterns. The aim of this article is to supply a detailed description of such a method. An example of its application is given. DESIGN: A statistical test is presented that retains the information on the connection of time periods by describing the seasonal pattern as one sine and one cosine function. Such functions can be included into a regression model. The resulting form of the seasonal pattern follows a cosine function with variable amplitude and shift. MAIN RESULTS: The test is shown to be applicable to test for seasonality. Not only one cosine function per time period, but also a mixture of cosine functions can be used to describe the seasonal pattern. Adjustment for confounding effects is possible. CONCLUSIONS: This method for studying seasonal patterns can be applied easily in a regression model. Adjusted prevalences and odds ratios can be calculated.