Self-controlled case series analyses: Small-sample performance
Self-controlled case series analyses: Small-sample performance
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DOI：
10.1016/j.csda.2007.06.016
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发表时间：
2008-01-10
影响因子：
1.8
通讯作者：
Farrington, C. Paddy
中科院分区：
文献类型：
--
作者：
Musonda, Patrick;Hocine, Mounia N.;Farrington, C. Paddy
在一个简化的情形下，导出了自控病例序列模型对数相对关联估计量的渐近偏差和方差的二阶表达式。研究了相对发病率、风险与观察期之比等因素对偏差和方差的影响。通过仿真研究了该估计器在实际场景中的小样本性能。研究发现，在实际中可能出现的情况下，根据风险期与观察期的比率和相对发病率，渐近方法对超过20-50个案例的数量是有效的。文中还讨论了蒙特卡罗方法在病例序列自身对照分析中的应用。(C)2007 Elsevier B.V.所有比赛已预订。
Second-order expressions for the asymptotic bias and variance of the log relative incidence estimator are derived for the self-controlled case series model in a simplified scenario. The dependence of the bias and variance on factors such as the relative incidence and ratio of risk to observation period are studied. Small-sample performance of the estimator in realistic scenarios is investigated using simulations. It is found that, in scenarios likely to arise in practice, asymptotic methods are valid for numbers of cases in excess of 20-50 depending on the ratio of the risk period to the observation period and on the relative incidence. The application of Monte Carlo methods to self-controlled case series analyses is also discussed. (C) 2007 Elsevier B.V. All fights reserved.