Rogerson P A
Department of Geography and National Center for Geographic Information and Analysis, State University of New York at Buffalo, Buffalo, NY 14261, USA.
Int J Epidemiol. 1996 Jun;25(3):644-8. doi: 10.1093/ije/25.3.644.
Hewitt's statistic for seasonality in monthly data is the maximal rank sum among all possible rank sums derived using consecutive 6-month periods. In this paper, Hewitt's test is extended to include those instances where 3, 4 or 5-month pulses or periods of raised incidence are hypothesized.
Monte Carlo methods are used to drive the approximate distribution of the test statistic under the null hypothesis, when the length of the hypothesized period is k = 3, 4, or 5. A combinatorial method is used to derive exact levels for the test statistic. The test is applied to monthly data on adolescent suicide. Finally, the power of the test is compared with the chi2 statistic using Monte Carlo simulation.
The distribution of the test statistic was found and used to test the null hypothesis of no seasonal variation in monthly adolescent suicides, using a period of k = 3 months. The null hypothesis was rejected, indicating seasonality in the data. Monte Carlo simulations show the test statistic to be more powerful than the chi2 statistic when sample sizes are small.
This generalization of Hewitt's test should be most useful in those instances where the researcher wishes to carry out a quick and simple test of the null hypothesis of no seasonality against the alternative of a predetermined 3, 4, or 5 month period of raised incidence. When there is no a priori hypothesis about the appropriate length of period.
休伊特针对月度数据季节性的统计量是在使用连续6个月周期得出的所有可能秩和中的最大秩和。在本文中，休伊特检验被扩展到包括那些假设存在3、4或5个月的脉冲或发病率上升期的情况。
当假设周期长度为k = 3、4或5时，使用蒙特卡罗方法来推导原假设下检验统计量的近似分布。使用组合方法来推导检验统计量的精确水平。该检验应用于青少年自杀的月度数据。最后，通过蒙特卡罗模拟将该检验的功效与卡方统计量进行比较。
找到了检验统计量的分布，并用于检验青少年自杀月度数据不存在季节性变化的原假设，使用的周期为k = 3个月。原假设被拒绝，表明数据存在季节性。蒙特卡罗模拟表明，当样本量较小时，检验统计量比卡方统计量更具功效。
休伊特检验的这种推广在研究人员希望针对发病率上升的预定3、4或5个月周期的备择假设，对不存在季节性的原假设进行快速简单检验的情况下应该最为有用。当对于合适的周期长度没有先验假设时。
