Abstract
We consider the statistical inference for right-censored data when censoring indicators are missing but nonignorable, and propose an adjusted imputation product-limit estimator. The proposed estimator is shown to be consistent and converges to a Gaussian process. Furthermore, we develop an empirical process-based testing method to check the MAR (missing at random) mechanism, and establish asymptotic properties for the proposed test statistic. To determine the critical value of the test, a consistent model-based bootstrap method is suggested. We conduct simulation studies to evaluate the numerical performance of the proposed method and compare it with existing methods. We also analyze a real data set from a breast cancer study for an illustration.
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Sun, Z., Xie, T. & Liang, H. Statistical inference for right-censored data with nonignorable missing censoring indicators. Sci. China Math. 56, 1263–1278 (2013). https://doi.org/10.1007/s11425-012-4492-x
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DOI: https://doi.org/10.1007/s11425-012-4492-x