Pulkstenis E, Ten Have T R, Landis J R
C. L. McIntosh & Associates, 12300 Twinbrook Parkway, Suite 625, Rockville, MD 20852, USA.
Stat Med. 2001 Feb 28;20(4):601-22. doi: 10.1002/sim.696.
We extend the model of Pulkstenis et al. that models binary longitudinal data, subject to informative drop-out through remedication, to the ordinal response case. We present a selection model shared-parameter approach that specifies mixed models for both ordinal response and discrete survival time to remedication. In this fashion, the random parameter present in both models completely characterizes the relationship between response and time to remedication inducing their conditional independence. With a log-log link function for both response and study 'survival', as well as specification of a log-gamma distribution for the random effect, we obtain a closed-form expression for the marginal log-likelihood of response and time to remedication that does not require approximation or numerical integration techniques. A data analysis is performed and simulation results presented which support the consistency of parameter and standard error estimates.
我们将Pulkstenis等人的模型进行了扩展，该模型用于对二元纵向数据进行建模，且存在因再次治疗导致的信息删失情况，我们将其扩展到了有序响应情形。我们提出了一种选择模型共享参数方法，该方法为有序响应和离散生存时间到再次治疗指定了混合模型。通过这种方式，两个模型中存在的随机参数完全刻画了响应与再次治疗时间之间的关系，从而诱导出它们的条件独立性。对于响应和研究“生存”均使用对数-对数链接函数，以及对随机效应指定对数伽马分布，我们得到了响应和再次治疗时间的边际对数似然的闭式表达式，该表达式不需要近似或数值积分技术。我们进行了数据分析并展示了模拟结果，这些结果支持了参数估计和标准误差估计的一致性。
