Analysing covariates with spike at zero: A modified FP procedure and conceptual issues
Analysing covariates with spike at zero: A modified FP procedure and conceptual issues
复制标题
DOI：
10.1002/bimj.201100263
复制
发表时间：
2012-09-01
影响因子：
1.7
通讯作者：
Sauerbrei, Willi
中科院分区：
文献类型：
--
作者：
Becher, Heiko;Lorenz, Eva;Sauerbrei, Willi
在流行病学和临床研究中，危险因素往往具有特殊的分布。一种常见的情况是，有一部分人的暴露为零，而在暴露的人中，我们有一些连续的分布。我们把这称为零点峰值。这方面的例子包括吸烟、哺乳时间或饮酒。此外，由于测量的检测下限较低，实验值和其他测量的经验分布可能具有半连续分布。为了模拟剂量响应函数，最近提出了一种扩展的分数多项式方法。在这篇文章中，我们建议对先前建议的FP手术进行修改。我们首先通过对相关分布类的研究，给出了这种修正方法的理论证明。在此，我们在Logistic回归模型的框架下，系统地推导了在给定的分布假设(正态、对数正态、伽马)下剂量-响应曲线的理论形状。此外，我们在模拟研究中检查了该程序的性能，并将其与先前建议的方法进行了比较，最后，我们用乳腺癌病例对照研究的数据说明了该程序。
In epidemiology and in clinical research, risk factors often have special distributions. A common situation is that a proportion of individuals have exposure zero, and among those exposed, we have some continuous distribution. We call this a spike at zero. Examples for this are smoking, duration of breastfeeding, or alcohol consumption. Furthermore, the empirical distribution of laboratory values and other measurements may have a semi-continuous distribution as a result of the lower detection limit of the measurement. To model the doseresponse function, an extension of the fractional polynomial approach was recently proposed. In this paper, we suggest a modification of the previously suggested FP procedure. We first give the theoretical justification of this modified procedure by investigating relevant distribution classes. Here, we systematically derive the theoretical shapes of doseresponse curves under given distributional assumptions (normal, log normal, gamma) in the framework of a logistic regression model. Further, we check the performance of the procedure in a simulation study and compare it to the previously suggested method, and finally we illustrate the procedures with data from a casecontrol study on breast cancer.