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

Grace Y. Yi, Yanyuan Ma, Raymond J. Carroll

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

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.
Original languageEnglish (US)
Pages (from-to)151-165
Number of pages15
JournalBiometrika
Volume99
Issue number1
DOIs
StatePublished - Feb 2 2012
Externally publishedYes

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Applied Mathematics
  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Mathematics(all)
  • Agricultural and Biological Sciences (miscellaneous)

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