MAXIMUM-LIKELIHOOD-ESTIMATION OF THE ATTRIBUTABLE FRACTION FROM LOGISTIC-MODELS
MAXIMUM-LIKELIHOOD-ESTIMATION OF THE ATTRIBUTABLE FRACTION FROM LOGISTIC-MODELS
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DOI：
10.2307/2532206
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发表时间：
1993-09-01
期刊：
影响因子：
1.9
通讯作者：
DRESCHER, K
中科院分区：
文献类型：
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作者：
GREENLAND, S;DRESCHER, K
Bruzzi等人（1985，American Journal of Epidemiology 122，904-914）提供了病例对照数据的可归因分数的基于一般逻辑模型的估计量，Benichou和Gail（1990，Biometrics 46，991-1003）给出了该估计量的隐式delta方法方差公式。然而，Bruzzi等人的估计量不是基于模型的最大似然估计量（MLE），因为它只使用模型来构建相对风险估计，而不是协变量分布。估算在这里，我们提供了队列和病例对照研究中归因分数的最大似然估计，以及它们的渐近方差。病例对照估计量推广了Drescher和Schill（1991，Biometrics 47，1247-1256）的估计量。我们还提出了一个有限的模拟研究，证实了早期的工作，更好的小样本性能时，置信区间是集中在对数变换点估计，而不是原始点估计。
Bruzzi et al. (1985, American Journal of Epidemiology 122, 904-914) provided a general logistic-model-based estimator of the attributable fraction for case-control data, and Benichou and Gail (1990, Biometrics 46, 991-1003) gave an implicit-delta-method variance formula for this estimator. The Bruzzi et al. estimator is not, however, the maximum likelihood estimator (MLE) based on the model, as it uses the model only to construct the relative risk estimates, and not the covariate-distribution. estimate. We here provide maximum likelihood estimators for the attributable fraction in cohort and case-control studies, and their asymptotic variances. The case-control estimator generalizes the estimator of Drescher and Schill (1991, Biometrics 47, 1247-1256). We also present a limited simulation study which confirms earlier work that better small-sample performance is obtained when the confidence interval is centered on the log-transformed point estimator rather than the original point estimator.