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首页> 外文期刊>Journal of applied statistics >The cross-product ratio in bivariate lognormal and gamma distributions, with an application to non-randomized trials
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The cross-product ratio in bivariate lognormal and gamma distributions, with an application to non-randomized trials

机译:双变量对数正态分布和gamma分布中的叉积比,适用于非随机试验

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摘要

Non-randomized trials can give a biased impression of the effectiveness of any intervention. We consider trials in which incidence rates are compared in two areas over two periods. Typically, one area receives an intervention, whereas the other does not. We outline and illustrate a method to estimate the bias in such trials under two different bivariate models. The illustrations use data in which no particular intervention is operating. The purpose is to illustrate the size of the bias that could be observed purely due to regression towards the mean (RTM). The illustrations show that the bias can be appreciably different from zero, and even when centred on zero, the variance of the bias can be large. We conclude that the results of non-randomized trials should be treated with caution, as interventions which show small effects could be explained as artefacts of RTM.
机译:非随机试验可能会给人以任何干预效果的偏见。我们考虑在两个时期内比较两个地区的发病率的试验。通常,一个地区接受干预,而另一地区则不接受。我们概述并说明了一种在两种不同的双变量模型下估算此类试验中偏倚的方法。插图使用的数据中没有进行任何特殊干预。目的是说明纯粹由于向均值(RTM)回归而可以观察到的偏差的大小。这些插图显示,偏差可能与零明显不同,并且即使以零为中心,偏差的变化也可能很大。我们得出的结论是,应谨慎对待非随机试验的结果,因为干预措施显示出较小的影响,可以解释为RTM的假象。

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