Estimation in semiparametric transition measurement error models for longitudinal data.


Journal Article

We consider semiparametric transition measurement error models for longitudinal data, where one of the covariates is measured with error in transition models, and no distributional assumption is made for the underlying unobserved covariate. An estimating equation approach based on the pseudo conditional score method is proposed. We show the resulting estimators of the regression coefficients are consistent and asymptotically normal. We also discuss the issue of efficiency loss. Simulation studies are conducted to examine the finite-sample performance of our estimators. The longitudinal AIDS Costs and Services Utilization Survey data are analyzed for illustration.

Full Text

Cited Authors

  • Pan, W; Zeng, D; Lin, X

Published Date

  • September 2009

Published In

Volume / Issue

  • 65 / 3

Start / End Page

  • 728 - 736

PubMed ID

  • 19173696

Pubmed Central ID

  • 19173696

Electronic International Standard Serial Number (EISSN)

  • 1541-0420

International Standard Serial Number (ISSN)

  • 0006-341X

Digital Object Identifier (DOI)

  • 10.1111/j.1541-0420.2008.01173.x


  • eng