Estimating Equations for Hazard Ratio Parameters Based on Correlated Failure Time Data
提出了加权偏似然估计方程来估计相关失效时间数据中的边际风险比参数，并推导了其渐近分布理论，模拟显示仅当失效时间相关性较强时加权才有显著效率提升。
Weighted partial likelihood estimating equations are proposed for the estimation of marginal hazard ratio parameters based on correlated failure time data. Asymptotic distribution theory is derived for the solution to such equations using martingale convergence results and inverse function theory. Simulation studies and theoretical efficiency calculations indicate that the inclusion of weights in the estimating equation produces important efficiency gains only if the dependencies among the failure times are strong.