×

Semiparametric analysis for competing risk data under the accelerated failure time model with missing cause failure. (Chinese. English summary) Zbl 1463.62090

Summary: This paper analyzes competing risks data with missing cause of failure under the accelerated failure time model. The missing mechanism is assumed to be missing at random. None parametric model for the probability of missing cause of failure is constructed. The inverse probability weighted and double robust techniques are used to modify the rank based estimating functions. Kernel smoothing technique is used to estimate the probability of missing cause of failure. The algorithm for the estimating equations is developed through transforming the estimating equations into an optimization problem. The asymptotic properties of the proposed estimators are established. A simulation study is carried out to evaluate the performance of the estimators. The proposed estimating method is illustrated by breast cancer data.

MSC:

62G05 Nonparametric estimation
62G20 Asymptotic properties of nonparametric inference
PDFBibTeX XMLCite