Gámiz ML, Mammen E, Martínez-Miranda MD, Nielsen JP. Missing link survival analysis with applications to available pandemic data.
Comput Stat Data Anal 2021;
169:107405. [PMID:
34924652 PMCID:
PMC8666881 DOI:
10.1016/j.csda.2021.107405]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 11/25/2021] [Accepted: 11/27/2021] [Indexed: 11/18/2022]
Abstract
It is shown how to overcome a new missing data problem in survival analysis. Iterative nonparametric techniques are utilized and the missing data information is both estimated and used for further estimation in each iterative step. Theory is developed and a good finite sample performance is illustrated by simulations. The main motivation is an application to French data on the temporal development of the number of hospitalized Covid-19 patients.
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