Fitting stratified proportional odds models by amalgamating conditional likelihoods.
Fitting stratified proportional odds models by amalgamating conditional likelihoods.
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DOI：
10.1002/sim.3325
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发表时间：
2008-10-30
影响因子：
2
通讯作者：
Sanchez, Brisa N.
中科院分区：
文献类型：
--
作者：
Mukherjee, Bhramar;Ahn, Jaeil;Liu, Ivy;Rathouz, Paul J.;Sanchez, Brisa N.
将变截距Logistic回归模型拟合到分层数据的经典方法是基于条件似然原理来消除地层特有的干扰参数。当结果变量具有多个有序类别时，结果模型的自然选择是分层比例优势或累积Logit模型。然而，经典的条件技术不适用于具有不同地层特定截距的一般K-分类累积Logit模型(K>；2)，因为不存在因满足而减少；滋扰参数保持在条件似然中。我们提出了一种通过合并从有序标度的所有可能的二进制折叠获得的条件似然来拟合分层比例赔率模型的方法。该方法允许在一般回归框架中使用分类协变量和连续协变量。我们给出了所提出的估计量的方差的稳健夹心估计。对于二元暴露，我们证明了我们的方法与文献中已经提出的估计量是等价的。建议的配方可以在标准软件中非常容易地实现。我们通过三个与生物医学研究相关的真实数据实例来说明这些方法。文中还给出了该方法与随机效应模型对分层参数影响的仿真结果。
Classical methods for fitting a varying intercept logistic regression model to stratified data are based on the conditional likelihood principle to eliminate the stratum-specific nuisance parameters. When the outcome variable has multiple ordered categories, a natural choice for the outcome model is a stratified proportional odds or cumulative logit model. However, classical conditioning techniques do not apply to the general K-category cumulative logit model (K > 2) with varying stratum-specific intercepts as there is no reduction due to suffciency; the nuisance parameters remain in the conditional likelihood. We propose a methodology to fit stratified proportional odds model by amalgamating conditional likelihoods obtained from all possible binary collapsing of the ordinal scale. The method allows for categorical and continuous covariates in a general regression framework. We provide a robust sandwich estimate of the variance of the proposed estimator. For binary exposures, we show equivalence of our approach to the estimators already proposed in the literature. The proposed recipe can be implemented very easily in standard software. We illustrate the methods via three real data examples related to biomedical research. Simulation results comparing the proposed method with a random effects model on the stratification parameters are also furnished.
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