Tracing studies in cohorts with attrition: Selection models for efficient sampling
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Date
2018-07-10
Authors
Moon, Nathalie C.
Zeng, Leilei
Cook, Richard J.
Journal Title
Journal ISSN
Volume Title
Publisher
Wiley
Abstract
Cohort studies of chronic diseases involve recruitment and longitudinal followup of affected individuals with a view to studying the effect of risk factors on disease progression and death. When the time to withdrawal from the cohort is conditionally independent of the disease process the primary consequence is a loss of information on the parameters of interest. This loss can sometimes
be mitigated through the conduct of tracing studies in which a subsample of those lost to follow up are contacted and some information is obtained on their disease and survival status. We describe the use of selection models to sample individuals for tracing who will yield more efficient estimators than those obtained by simple random sampling. Efficient sampling schemes featuring cost constraints are also developed and shown to perform well. An application to data from the University of Toronto Psoriatic Arthritis Cohort illustrates how to apply the method in a real setting.
Description
This is the peer reviewed version of the following article: Nathalie C. Moon, Leilei Zeng and Richard J. Cook, Tracing studies in cohorts with attrition: Selection models for efficient sampling, Statistics in Medicine (2018), 37(15): 2354–2366 which has been published in final form at https://doi.org/10.1002/sim.7646. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.
Keywords
attrition, inception cohort, Markov model, selection model, sequentially missing at random, tracing