Nonparametric regression of state occupation, entry, exit, and waiting times with multistate right-censored data.

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ID: 60614
2013
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Abstract
We construct nonparametric regression estimators of a number of temporal functions in a multistate system based on a continuous univariate baseline covariate. These estimators include state occupation probabilities, state entry, exit, and waiting (sojourn) time distribution functions of a general progressive (e.g., acyclic) multistate model. We subject the data to right censoring, and the censoring mechanism is explainable by observable covariates that could be time dependent. The resulting estimators are valid even if the multistate process is non-Markov. We study the performance of the estimators in two simulation settings. We establish large sample consistency of these estimators. We illustrate our estimators using a data set on bone marrow transplant recipients.
Reference Key
mostajabi2013nonparametricstatistics Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Mostajabi, Farida;Datta, Somnath;
Journal Statistics in Medicine
Year 2013
DOI
10.1002/sim.5703
URL
Keywords
multistate models bone marrow transplant nonparametric regression right censoring sojourn times state occupation probabilities

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