A general binomial regression model to estimate standardized risk differences from binary response data.
A general binomial regression model to estimate standardized risk differences from binary response data.
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DOI：
10.1002/sim.5553
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发表时间：
2013-02-28
影响因子：
2
通讯作者：
Katki, Hormuzd A.
中科院分区：
文献类型：
--
作者：
Kovalchik, Stephanie A.;Varadhan, Ravi;Fetterman, Barbara;Poitras, Nancy E.;Wacholder, Sholom;Katki, Hormuzd A.
对绝对风险和风险差异的估计对于评估生物医学研究结果的临床和人群影响是必要的。我们已经开发了一个线性expit回归模型（LEXPIT），将线性和非线性风险效应，以估计绝对风险的研究的二元结果。LEXPIT是二项线性和逻辑回归模型的推广。LEXPIT线性项的系数估计调整后的风险差异，而取幂的非线性项估计剩余优势比。的LEXPIT可能是特别有用的流行病学研究的风险关联，其中调整多个混杂变量是常见的。我们提出了一个约束最大似然估计算法，确保风险估计的LEXPIT模型的可行性，并描述程序定义的可行区域的参数空间，判断收敛性，并评估边界的情况下。仿真结果表明，该方法是计算鲁棒性，并产生可行的，一致的估计。我们应用LEXPIT模型评估了在北方加州Kaiser Permanente接受筛查的167，171名妇女中与不同Pap和人乳头瘤病毒检测结果相关的宫颈癌前病变或癌症的绝对5年风险。LEXPIT模型发现，HPV阴性患者的异常巴氏试验导致风险增加，而logistic回归未检测到。我们的R软件包blm提供了用于拟合LEXPIT模型的免费易用软件。
Estimates of absolute risks and risk differences are necessary for evaluating the clinical and population impact of biomedical research findings. We have developed a linear-expit regression model (LEXPIT) to incorporate linear and nonlinear risk effects to estimate absolute risk from studies of a binary outcome. The LEXPIT is a generalization of both the binomial linear and logistic regression models. The coefficients of the LEXPIT linear terms estimate adjusted risk differences, while the exponentiated nonlinear terms estimate residual odds ratios. The LEXPIT could be particularly useful for epidemiological studies of risk association, where adjustment for multiple confounding variables is common. We present a constrained maximum likelihood estimation algorithm that ensures the feasibility of risk estimates of the LEXPIT model and describe procedures for defining the feasible region of the parameter space, judging convergence, and evaluating boundary cases. Simulations demonstrate that the methodology is computationally robust and yields feasible, consistent estimators. We applied the LEXPIT model to estimate the absolute five-year risk of cervical precancer or cancer associated with different Pap and human papillomavirus test results in 167,171 women undergoing screening at Kaiser Permanente Northern California. The LEXPIT model found an increased risk due to abnormal Pap test in HPV-negative that was not detected with logistic regression. Our R package blm provides free and easy-to-use software for fitting the LEXPIT model.
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影响因子：
1.9
作者：
Scheike, TH;Zhang, MJ
通讯作者：
Zhang, MJ
影响因子：
51.1
作者：
Katki, Hormuzd A.;Kinney, Walter K.;Fetterman, Barbara;Lorey, Thomas;Poitras, Nancy E.;Cheung, Li;Demuth, Franklin;Schiffman, Mark;Wacholder, Sholom;Castle, Philip E.
通讯作者：
Castle, Philip E.
影响因子：
1.5
作者：
AMEMIYA, T
通讯作者：
AMEMIYA, T
影响因子：
5
作者：
GREENLAND, S
通讯作者：
GREENLAND, S
影响因子：
1.8
作者：
Long, Qi;Chung, Matthias;Johnson, Brent A.
通讯作者：
Johnson, Brent A.