Journal article

Sensitivity analysis within multiple imputation framework using delta-adjustment: Application to Longitudinal Study of Australian Children

Panteha Hayati Rezvan, Katherine J Lee, Julie A Simpson

Longitudinal and Life Course Studies | SOC LONGITUDINAL & LIFE COURSE STUDIES | Published : 2018

Abstract

Multiple imputation (MI) is a powerful statistical method for handling missing data. Standard implementations of MI are valid under the unverifiable assumption of missing at random (MAR), which is often implausible in practice. The delta-adjustment method, implemented within the MI framework, can be used to perform sensitivity analyses that assess the impact of departures from the MAR assumption on the final inference. This method requires specification of unknown sensitivity parameter(s) (termed as delta(s)). We illustrate the application of the delta-adjustment method using data from the Longitudinal Study of Australian Children, where the epidemiological question is to estimate the associ..

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Grants

Awarded by National Health and Medical Research Council


Awarded by National Institute of Mental Health (NIMH)


Awarded by UCLA Center for HIV Identification, Prevention, and Treatment Services (CHIPTS)


Funding Acknowledgements

This work was supported by funding from the National Health and Medical Research Council: a Centre of Research Excellence grant, ID 1035261, awarded to the Victorian Centre of Biostatistics (ViCBiostat), Career Development Fellowship ID 1053609 (KJL), and Senior Research Fellowship ID 1104975 (JAS). PHR was funded by a University of Melbourne International Research Scholarship (MIRS). She is currently funded by National Institute of Mental Health (NIMH) [grant number: 1T32MH109205-01A1] and the UCLA Center for HIV Identification, Prevention, and Treatment Services (CHIPTS) grant (P30MH58107).