ArticleBernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability2022
Nonparametric inference for reversed mean models with panel count data.
Article in Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Semiparametric regression of panel count data with informative terminal event.Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability · 2023Article
- Nonparametric inference for reversed mean models with panel count data.Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability · 2022Article
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Authors and funding
5 authors.
Funding
Abstract
Panel count data typically refer to data arising from studies with recurrent events, in which subjects are observed only at discrete time points rather than under continuous observations. We investigate a general situation where a recurrent event process is eventually truncated by an informative terminal event and we are particularly interested in behaviors of the recurrent event process near the terminal event. We propose a reversed mean model for estimating the mean function of the recurrent event process. We develop a two-stage sieve likelihood-based method to estimate the mean function, which overcomes the computational difficulties arising from a nuisance functional parameter involved in the likelihood. The consistency and the convergence rate of the two-stage estimator are established. Allowing for the convergence rate slower than the standard rate, we develop the general weak convergence theory of
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.