Chambaz Antoine, Choudat Dominique, Huber Catherine, Pairon Jean-Claude, van der Laan Mark J
Modal'X, Université Paris Ouest Nanterre, 92001 Nanterre.
Biostatistics. 2014 Apr;15(2):327-40. doi: 10.1093/biostatistics/kxt042. Epub 2013 Oct 9.
We analyze the effect of occupational exposure to asbestos on the occurrence of lung cancer based on a recent French case-control (CC) study. We build a large collection of threshold regression models, data-adaptively select a better model by CC-weighted likelihood-based cross-validation and then fit this better model by CC-weighted maximum likelihood. The CC-weighting allows us to draw valid inferences from CC data without relying on a logistic regression. This is possible because the joint distribution of the indicator of being a case and matching variable is available beforehand owing to two studies independent from our data set. The implications of the fitted model in terms of years of life free of lung cancer lost due to the exposure to asbestos are discussed.
我们基于最近一项法国病例对照（CC）研究，分析职业性接触石棉对肺癌发生的影响。我们构建了大量阈值回归模型，通过基于CC加权似然的交叉验证数据自适应地选择一个更好的模型，然后通过CC加权最大似然法拟合这个更好的模型。CC加权使我们能够从CC数据中得出有效的推断，而无需依赖逻辑回归。这是可行的，因为由于两项独立于我们数据集的研究，病例指标和匹配变量的联合分布是预先已知的。我们还讨论了拟合模型在因接触石棉而导致无肺癌生存年数损失方面的意义。
