In medical research, the results from seasonality analyses provide valuable information that eventually can help to clarify the etiology of poorly understood diseases. We present a Bayesian procedure for the analysis of seasonal variation in medical data. The method is a Bayesian version of a frequentist test that performs very well. Statistical seasonality analyses of medical data often involve a short time series, 12 observations with small amplitude and small sample size. Among the specialized procedures already developed for such analyses, only one is Bayesian; the method we present in this paper appears to be the second such Bayesian procedure. Easy to understand and apply, the method is versatile because it can be used to analyze different types of seasonal variation. We illustrate the procedure’s application with two examples of real data.

中文翻译：

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医学数据季节性的贝叶斯检验

在医学研究中，季节性分析的结果提供了有价值的信息，最终有助于阐明知之甚少的疾病的病因。我们提出了一个贝叶斯程序来分析医学数据的季节性变化。该方法是贝叶斯版本的常客测试，表现非常好。医学数据的统计季节性分析通常涉及短时间序列、12 个小幅值和小样本量的观测值。在已经为此类分析开发的专门程序中，只有一个是贝叶斯；我们在本文中提出的方法似乎是第二个这样的贝叶斯程序。该方法易于理解和应用，用途广泛，可用于分析不同类型的季节性变化。我们用两个真实数据的例子来说明这个过程的应用。