Nam J M
Biostatistics Branch, National Cancer Institute, Rockville, Maryland 20892, USA.
Biometrics. 1995 Dec;51(4):1411-7.
The statistical analysis for detecting a seasonal trend in epidemiologic studies has traditionally employed Edwards' method (1961, Annals of Human Genetics 25, 83-85) or a modification (Roger, 1977, Biometrika 64, 152-155) which are formulated under a simple harmonic model with two parameters, amplitude and phase angle. In seasonality studies, researchers usually have known seasons at which peak and trough incidences occur. Utilizing this information, we present the most efficient interval estimation of the ratio of maximum and minimum seasonal frequencies and the uniformly most powerful unbiased test for detecting the seasonal variation using the general theory of Bartlett (1953, Biometrika 40, 12-19). The asymptotic power function and the approximate formula for sample size are derived. A simulation study shows that actual values of power of this score test are satisfactorily close to nominal values even for small samples. The proposed simple score test is more powerful and requires substantially smaller samples for a specific power than the standard Edwards or Roger tests. An alternative method based on the logarithm of the maximum likelihood estimator of the ratio is comparable to the simple score method.
在流行病学研究中，用于检测季节性趋势的统计分析传统上采用爱德华兹方法（1961年，《人类遗传学纪事》25卷，第83 - 85页）或其一种改进方法（罗杰，1977年，《生物统计学》64卷，第152 - 155页），这些方法是在具有两个参数（幅度和相位角）的简单谐波模型下制定的。在季节性研究中，研究人员通常已知高峰和低谷发病率出现的季节。利用这些信息，我们使用巴特利特的一般理论（1953年，《生物统计学》40卷，第12 - 19页），给出了最大和最小季节频率之比的最有效区间估计以及用于检测季节变化的一致最强大无偏检验。推导了渐近功效函数和样本量的近似公式。一项模拟研究表明，即使对于小样本，该得分检验的实际功效值也令人满意地接近名义值。所提出的简单得分检验比标准的爱德华兹或罗杰检验更具功效，并且对于特定功效所需的样本量要小得多。基于该比率的最大似然估计量的对数的另一种方法与简单得分方法相当。
