Bias control in the analysis of case-control studies with incidence density sampling
Bias control in the analysis of case-control studies with incidence density sampling
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DOI：
10.1093/ije/dyz116
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发表时间：
2019-12-01
影响因子：
7.7
通讯作者：
Milligan, Paul
中科院分区：
文献类型：
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作者：
Cheung, Yin Bun;Ma, Xiangmei;Milligan, Paul
背景资料：以前的病例对照研究设计的模拟研究使用发病率密度抽样，需要个体匹配的时间，显示有偏倚的估计关联的条件Logistic回归（logistic回归）分析;然而，这是未知的原因。另外，在使用排他抽样设计的病例对照研究分析中，已经表明，调整单独匹配的二元因素的无条件logistic回归（ULR）可以给出无偏估计。这种分析方法在发病率密度sampling的有效性需要evaluation.Methods：在广泛的模拟使用发病率密度抽样，我们评估了各种分析方法：ESTA有和没有一个偏差减少的方法，ULR与调整时间在五分位数（和剩余时间内五分位数）和ULR与调整匹配集和偏差减少。我们重新分析了病例对照研究的B型流感嗜血杆菌疫苗using these methods.Results：我们发现，从以前的研究中的偏差的分析是由于稀疏的数据偏差。可通过偏倚减少法或增加病例和/或对照的数量来控制。ULR与五分位数的时间调整通常给出的结果高度可比的，尽管打破了比赛。在影响随时间变化的情况下，需要进一步调整剩余时间趋势。ULR与匹配集的调整往往表现不佳，尽管偏差reduction.Conclusions：使用发病率密度抽样的研究可以分析ULR与调整时间或时间，可能与偏差减少。
Background: Previous simulation studies of the case-control study design using incidence density sampling, which required individual matching for time, showed biased estimates of association from conditional logistic regression (CLR) analysis; however, the reason for this is unknown. Separately, in the analysis of case-control studies using the exclusive sampling design, it has been shown that unconditional logistic regression (ULR) with adjustment for an individually matched binary factor can give unbiased estimates. The validity of this analytic approach in incidence density sampling needs evaluation.Methods: In extensive simulations using incidence density sampling, we evaluated various analytic methods: CLR with and without a bias-reduction method, ULR with adjustment for time in quintiles (and residual time within quintiles) and ULR with adjustment for matched sets and bias reduction. We re-analysed a case-control study of Haemophilus influenzae type B vaccine using these methods.Results: We found that the bias in the CLR analysis from previous studies was due to sparse data bias. It can be controlled by the bias-reduction method for CLR or by increasing the number of cases and/or controls. ULR with adjustment for time in quintiles usually gave results highly comparable to CLR, despite breaking the matches. Further adjustment for residual time trends was needed in the case of time-varying effects. ULR with adjustment for matched sets tended to perform poorly despite bias reduction.Conclusions: Studies using incidence density sampling may be analysed by either ULR with adjustment for time or CLR, possibly with bias reduction.