Faculty of Business Administration, University of Macau, Macau, People's Republic of China.
Stat Med. 2011 Mar 30;30(7):725-41. doi: 10.1002/sim.4122. Epub 2010 Nov 30.
The CUSUM procedure has been popularly used for detecting a shift in the incidence rate of a rare health event. Many CUSUM methods are developed based on a Poisson model with a constant mean number of events. In practice, the expected number of events is likely to vary over time as the population size at risk is not constant but often grows over time. An increase in the baseline incidence rate tends to be masked by the population growth. To efficiently detect an increase in the baseline incidence rate, it is appealing to assign more weight to recent observations and less weight to older observations. This paper compares weighted CUSUM (WCUSUM) and conventional CUSUM procedures in the presence of monotone changes in population size. The simulation results show that the WCUSUM method may be more efficient than the conventional CUSUM methods in detecting increases in the incidence rate, especially for small shifts. An example based on mortality data from New Mexico is used to illustrate the implementation of the WCUSUM method.
CUSUM 程序已广泛用于检测罕见健康事件发生率的变化。许多 CUSUM 方法都是基于泊松模型开发的，该模型的平均事件数是常数。在实践中，由于风险人群数量不是固定的，而是随着时间的推移而不断增长，因此预期事件数很可能会随时间发生变化。基线发病率的增加往往会被人群增长所掩盖。为了有效地检测基线发病率的增加，给最近的观测值分配更多的权重，给旧的观测值分配更少的权重是很有吸引力的。本文在人口规模单调变化的情况下，比较了加权 CUSUM（WCUSUM）和传统 CUSUM 程序。模拟结果表明，WCUSUM 方法在检测发病率的增加方面可能比传统 CUSUM 方法更有效，尤其是对于较小的变化。基于新墨西哥州死亡率数据的一个例子说明了 WCUSUM 方法的实施。
