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On the use of the not-at-random fully conditional specification (NARFCS) procedure in practice

Tompsett, DM; Leacy, F; Moreno-Betancur, M; Heron, J; White, IR; (2018) On the use of the not-at-random fully conditional specification (NARFCS) procedure in practice. Statistics in Medicine 10.1002/sim.7643. (In press). Green open access

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Abstract

The not-at-random fully conditional specification (NARFCS) procedure provides a flexible means for the imputation of multivariable missing data under missing-not-at-random conditions. Recent work has outlined difficulties with eliciting the sensitivity parameters of the procedure from expert opinion due to their conditional nature. Failure to adequately account for this conditioning will generate imputations that are inconsistent with the assumptions of the user. In this paper, we clarify the importance of correct conditioning of NARFCS sensitivity parameters and develop procedures to calibrate these sensitivity parameters by relating them to more easily elicited quantities, in particular, the sensitivity parameters from simpler pattern mixture models. Additionally, we consider how to include the missingness indicators as part of the imputation models of NARFCS, recommending including all of them in each model as default practice. Algorithms are developed to perform the calibration procedure and demonstrated on data from the Avon Longitudinal Study of Parents and Children, as well as with simulation studies.

Type: Article
Title: On the use of the not-at-random fully conditional specification (NARFCS) procedure in practice
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1002/sim.7643
Publisher version: https://doi.org/10.1002/sim.7643
Language: English
Additional information: Copyright © 2018 The Authors. This is an open access article under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Keywords: ALSPAC, FCS, MICE, MNAR, multiple imputations
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Population, Policy and Practice Dept
URI: https://discovery.ucl.ac.uk/id/eprint/10047681
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