Cai J, Prentice R L
University of North Carolina, Chapel Hill, USA.
Lifetime Data Anal. 1997;3(3):197-213. doi: 10.1023/a:1009613313677.
Recent 'marginal' methods for the regression analysis of multivariate failure time data have mostly assumed Cox (1972) model hazard functions in which the members of the cluster have distinct baseline hazard functions. In some important applications, including sibling family studies in genetic epidemiology and group randomized intervention trials, a common baseline hazard assumption is more natural. Here we consider a weighted partial likelihood score equation for the estimation of regression parameters under a common baseline hazard model, and provide corresponding asymptotic distribution theory. An extensive series of simulation studies is used to examine the adequacy of the asymptotic distributional approximations, and especially the efficiency gain due to weighting, as a function of strength of dependency within cluster, and cluster size.
近期用于多变量失效时间数据回归分析的“边缘”方法大多假定采用考克斯（1972年）模型的风险函数，其中聚类成员具有不同的基线风险函数。在一些重要应用中，包括遗传流行病学中的同胞家庭研究和群组随机干预试验，共同基线风险假设更为自然。在此，我们考虑在共同基线风险模型下用于估计回归参数的加权偏似然得分方程，并提供相应的渐近分布理论。通过一系列广泛的模拟研究来检验渐近分布近似的充分性，特别是作为聚类内相依强度和聚类大小函数的加权效率增益。
