School of Mathematics and Statistics, The Open University, Milton Keynes, UK.
Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
Stat Med. 2018 Feb 20;37(4):643-658. doi: 10.1002/sim.7536. Epub 2017 Nov 2.
We describe some simple techniques for investigating 2 key assumptions of the self-controlled case series (SCCS) method, namely, that events do not influence subsequent exposures and that events do not influence the length of observation periods. For each assumption, we propose some simple tests based on the standard SCCS model, along with associated graphical displays. The methods also enable the user to investigate the robustness of the results obtained using the standard SCCS model to failure of assumptions. The proposed methods are investigated by simulations and applied to data on measles, mumps and rubella vaccine, and antipsychotics.
我们描述了一些简单的技术，用于调查自我对照病例系列（SCCS）方法的两个关键假设，即事件不会影响随后的暴露，并且事件不会影响观察期的长度。对于每个假设，我们基于标准 SCCS 模型提出了一些简单的测试，并附有相关的图形显示。这些方法还使用户能够研究使用标准 SCCS 模型对假设失败的结果的稳健性。通过模拟研究了所提出的方法，并将其应用于麻疹、腮腺炎和风疹疫苗和抗精神病药物的数据。
