Solis-Trapala I L, Farewell V T
Departamento de Probabilidad y Estadística, Centro de Investigación en Matemáticas, Guanajuato, Gto., México.
Stat Med. 2005 Aug 30;24(16):2557-75. doi: 10.1002/sim.2121.
A robust likelihood approach for the analysis of overdispersed correlated count data that takes into account cluster varying covariates is proposed. We emphasise two characteristics of the proposed method: That the correlation structure satisfies the constraints on the second moments and that the estimation of the correlation structure guarantees consistent estimates of the regression coefficients. In addition we extend the mean specification to include within- and between-cluster effects. The method is illustrated through the analysis of data from two studies. In the first study, cross-sectional count data from a randomised controlled trial are analysed to evaluate the efficacy of a communication skills training programme. The second study involves longitudinal count data which represent counts of damaged hand joints in patients with psoriatic arthritis. Motivated by this study, we generalize our model to accommodate for a subpopulation of patients who are not susceptible to the development of damaged hand joints.
提出了一种稳健似然方法，用于分析考虑聚类可变协变量的过度分散相关计数数据。我们强调所提方法的两个特征：相关结构满足对二阶矩的约束，以及相关结构的估计保证回归系数的一致估计。此外，我们扩展了均值设定，以纳入聚类内和聚类间效应。通过对两项研究的数据进行分析来说明该方法。在第一项研究中，分析了来自一项随机对照试验的横断面计数数据，以评估沟通技能培训计划的效果。第二项研究涉及纵向计数数据，这些数据代表银屑病关节炎患者手部关节损伤的计数。受该研究启发，我们对模型进行了推广，以适应不易发生手部关节损伤的亚组患者。
