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. 2012 Feb 2;99(1):151–165. doi: 10.1093/biomet/asr076

A functional generalized method of moments approach for longitudinal studies with missing responses and covariate measurement error

Grace Y Yi 1, Yanyuan Ma 2, Raymond J Carroll 3
PMCID: PMC5541954  NIHMSID: NIHMS586184  PMID: 28781377

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.

Keywords: Functional measurement error, Generalized method of moments, Inverse probability weighting, Longitudinal data, Measurement error, Missing response, Structural measurement error

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