A functional generalized method of moments approach for longitudinal studies with missing responses and covariate measurement error
Grace Y. Yi,
Yanyuan Ma and
Raymond J. Carroll
Biometrika, 2012, vol. 99, issue 1, 151-165
Abstract:
Covariate measurement error and missing responses are typical features in longitudinal data analysis. There has been extensive research on either covariate measurement error or missing responses, but relatively little work has been done to address both simultaneously. In this paper, we propose a simple method for the marginal analysis of longitudinal data with time-varying covariates, some of which are measured with error, while the response is subject to missingness. Our method has a number of appealing properties: assumptions on the model are minimal, with none needed about the distribution of the mismeasured covariate; implementation is straightforward and its applicability is broad. We provide both theoretical justification and numerical results. Copyright 2012, Oxford University Press.
Date: 2012
References: Add references at CitEc
Citations: View citations in EconPapers (13)
Downloads: (external link)
http://hdl.handle.net/10.1093/biomet/asr076 (application/pdf)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:oup:biomet:v:99:y:2012:i:1:p:151-165
Ordering information: This journal article can be ordered from
https://academic.oup.com/journals
Access Statistics for this article
Biometrika is currently edited by Paul Fearnhead
More articles in Biometrika from Biometrika Trust Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK.
Bibliographic data for series maintained by Oxford University Press ().