Fengling Ren

Wei Chen

For analyzing clustered survival data, a flexible partially linear additive hazards model is proposed. To accommodate the nonlinear effects, the unknown regression function is approximated by B-splines. All regression coefficients are estimated through a system of pseudo-score functions. Under certain conditions, the proposed estimators are shown to be asymptotically normal, where a consistent estimator of the covariance matrix is given. Simulation studies are also conducted to evaluate the finite sample performance of the proposed method, which is illustrated using a real data set from an AIDS clinical trial

PARTIALLY LINEAR ADDITIVE HAZARDS REGRESSION FOR CLUSTERED AND RIGHT CENSORED DATA

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