Premium Model‐assisted estimators for time‐to‐event data from complex surveys
Author(s)
Reist Benjamin M.,
Valliant Richard
Publication year2020
Publication title
statistics in medicine
Resource typeJournals
We develop model‐assisted estimators for complex survey data for the proportion of a population that experienced some event by a specified time t . Theory for the new estimators uses time‐to‐event models as the underlying framework but have both good model‐based and design‐based properties. The estimators are compared in a simulation to traditional survey estimation methods and are also applied to a study of nurses' health. The new estimators take advantage of covariates predictive of the event and reduce standard errors compared to conventional alternatives.
Subject(s)computer science , covariate , econometrics , engineering , estimation , estimator , event (particle physics) , event data , machine learning , mathematics , physics , quantum mechanics , small area estimation , statistics , systems engineering
Language(s)English
SCImago Journal Rank1.996
H-Index183
eISSN1097-0258
pISSN0277-6715
DOI10.1002/sim.8728

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