Juarez-Colunga E, Silva G L, Dean C B
Department of Biostatistics and Informatics, University of Colorado Denver, Aurora, Colorado 80045, U.S.A.
CEAUL and Department of Mathematics-IST, Universidade de Lisboa, Av. Rovisco Pais, 1, 1049-001 Lisboa, Portugal.
Biometrics. 2017 Dec;73(4):1413-1423. doi: 10.1111/biom.12691. Epub 2017 Mar 17.
Panel counts are often encountered in longitudinal, such as diary, studies where individuals are followed over time and the number of events occurring in time intervals, or panels, is recorded. This article develops methods for situations where, in addition to the counts of events, a mark, denoting a measure of severity of the events, is recorded. In many situations there is an association between the panel counts and their marks. This is the case for our motivating application that studies the effect of two hormone therapy treatments in reducing counts and severities of vasomotor symptoms in women after hysterectomy/ovariectomy. We model the event counts and their severities jointly through the use of shared random effects. We also compare, through simulation, the power of testing for the treatment effect based on such joint modeling and an alternative scoring approach, which is commonly employed. The scoring approach analyzes the compound outcome of counts times weighted severity. We discuss this approach and quantify challenges which may arise in isolating the treatment effect when such a scoring approach is used. We also show that the power of detecting a treatment effect is higher when using the joint model than analysis using the scoring approach. Inference is performed via Markov chain Monte Carlo methods.
在纵向研究（如日记研究）中经常会遇到面板计数，在这类研究中，个体被长期跟踪，并且记录在时间间隔（即面板）内发生的事件数量。本文针对这样的情况开发了一些方法，即在记录事件计数的同时，还记录一个表示事件严重程度的标记。在许多情况下，面板计数与其标记之间存在关联。我们的激励性应用就是如此，该应用研究两种激素疗法对子宫切除/卵巢切除术后女性血管舒缩症状的数量和严重程度的降低效果。我们通过使用共享随机效应来联合建模事件计数及其严重程度。我们还通过模拟比较了基于这种联合建模和一种常用的替代计分方法来检验治疗效果的功效。计分方法分析计数乘以加权严重程度的复合结果。我们讨论这种方法，并量化在使用这种计分方法时分离治疗效果可能出现的挑战。我们还表明，使用联合模型检测治疗效果的功效比使用计分方法进行分析更高。通过马尔可夫链蒙特卡罗方法进行推断。
