Likelihood Based Inference for Current Status Data on a Grid : a Boundary Phenomenon and an Adaptive Inference Procedure

@inproceedings{Tang2011LikelihoodBI,
  title={Likelihood Based Inference for Current Status Data on a Grid : a Boundary Phenomenon and an Adaptive Inference Procedure},
  author={Runlong Tang and Moulinath Banerjee and Michael R. Kosorok},
  year={2011}
}
In this paper, we study the nonparametric maximum likelihood estimator (NPMLE) for an event time distribution function at a point in the current status model with observation times supported on a grid of potentially unknown sparsity and with multiple subjects sharing the same observation time. This is of interest since observation time ties occur frequently with current status data. The grid resolution is specified as cn−γ with c > 0 being a scaling constant and γ > 0 regulating the sparsity of… CONTINUE READING