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Stratification for confounding--part 1: the Mantel-Haenszel formula

机译:混淆的层次化-第1部分:Mantel-Haenszel公式

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摘要

Stratification allows to control for confounding by creating two or more categories or subgroups in which the confounding variable either does not vary or does not vary very much. The Mantel-Haenszel formula is applied in cohort and in case-control studies to calculate an overall, unconfounded, effect estimate of a given exposure for a specific outcome by combining stratum-specific relative risks (RR) or odds ratios (OR). Stratum-specific RRs or ORs are calculated within each stratum of the confounding variable and compared with the corresponding effect estimates in the whole group (that is, with the unstratified RR or OR). The use of the Mantel-Haenszel formula presents some limitations: (1) if there is more than a single confounder, the application of this formula is laborious and demands a relatively large sample size, and (2) this method requires continuous confounders to be constrained into a limited number of categories thus potentially generating residual confounding (a phenomenon particularly relevant when the variable is categorized into few strata). In the stratified analysis, residual confounding can be minimized by increasing the number of strata, a possibility strictly dependent on sample size
机译:分层允许通过创建两个或多个类别或子组来控制混杂,其中混杂变量没有变化或变化不大。 Mantel-Haenszel公式用于队列研究和病例对照研究,通过结合特定于层的相对风险(RR)或优势比(OR)来计算特定结果对给定暴露的总体,无混淆的效果估计。在混杂变量的每个层次内计算特定于层的RR或OR,并将其与整个组中相应的效果估计值进行比较(即与未分层的RR或OR)。 Mantel-Haenszel公式的使用存在一些局限性:(1)如果存在多个单一的混杂因素,则此公式的应用很费力并且需要相对较大的样本量;(2)此方法需要连续混杂因素为限制在有限数量的类别中,因此有可能产生残余混淆(这种现象在将变量分类为几个层次时尤为重要)。在分层分析中,可以通过增加层数来最大程度地减少残留混杂,这可能严格取决于样本量

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