Evaluation of stability of directly standardized rates for sparse data using simulation methods
Evaluation of stability of directly standardized rates for sparse data using simulation methods
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DOI：
10.1186/s12963-018-0177-1
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发表时间：
2018-12-22
影响因子：
3.3
通讯作者：
Bestwick, Jonathan
中科院分区：
文献类型：
--
作者：
Morris, Joan K.;Tan, Joachim;Bestwick, Jonathan
背景：直接标准化比率（DSRs）针对不同人群的不同年龄分布进行调整，并使人们能够直接比较人群之间的发病率。它们是定期发布的，但有人担心，如果DSR是基于“少量”事件而发布的，那么它是无效的。本研究的目的是确定在分析英国真实数据时不应发表DSR的值。方法：采用标准蒙特卡罗模拟技术，假设19个年龄组(即0-4、5-9、…90年以上)遵循独立泊松分布。事件总数、年龄特定风险和每个年龄组的人口规模各不相同。对于每10,000次模拟，DSR（使用2013年欧洲标准人口权重）以及估计95%置信区间（ci）的三种不同方法（正态近似，Dobson和Tiwari修正伽马）的覆盖率进行了计算。结果：正如预期的那样，正态近似不适合在少于100个事件发生时使用。计算置信区间的Tiwari方法和Dobson方法产生了类似的估计，当预期或观察到的事件数量大于或等于10时，它们都适用。ci的准确性不受事件跨类别分布（即聚类程度、抽样人口的年龄分布以及未发生事件的类别数量）的影响。结论：当观察到的事件总数小于10时，不应给予DSRs。由于Dobson法的公式比Tiwari法简单，覆盖范围略准确，因此Dobson法可以被认为是首选方法。
Background: Directly standardized rates (DSRs) adjust for different age distributions in different populations and enable, say, the rates of disease between the populations to be directly compared. They are routinely published but there is concern that a DSR is not valid when it is based on a "small" number of events. The aim of this study was to determine the value at which a DSR should not be published when analyzing real data in England.Methods: Standard Monte Carlo simulation techniques were used assuming the number of events in 19 age groups (i.e., 0-4, 5-9, ... 90+ years) follow independent Poisson distributions. The total number of events, age specific risks, and the population sizes in each age group were varied. For each of 10,000 simulations the DSR (using the 2013 European Standard Population weights), together with the coverage of three different methods (normal approximation, Dobson, and Tiwari modified gamma) of estimating the 95% confidence intervals (CIs), were calculated.Results: The normal approximation was, as expected, not suitable for use when fewer than 100 events occurred. The Tiwari method and the Dobson method of calculating confidence intervals produced similar estimates and either was suitable when the expected or observed numbers of events were 10 or greater. The accuracy of the CIs was not influenced by the distribution of the events across categories (i.e., the degree of clustering, the age distributions of the sampling populations, and the number of categories with no events occurring in them).Conclusions: DSRs should not be given when the total observed number of events is less than 10. The Dobson method might be considered the preferred method due to the formulae being simpler than that of the Tiwari method and the coverage being slightly more accurate.