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Conditional estimation for generalized linear models when covariates are subject-specific parameters in a mixed model for longitudinal measurements.

Publication ,  Journal Article
Li, E; Zhang, D; Davidian, M
Published in: Biometrics
March 2004

The relationship between a primary endpoint and features of longitudinal profiles of a continuous response is often of interest, and a relevant framework is that of a generalized linear model with covariates that are subject-specific random effects in a linear mixed model for the longitudinal measurements. Naive implementation by imputing subject-specific effects from individual regression fits yields biased inference, and several methods for reducing this bias have been proposed. These require a parametric (normality) assumption on the random effects, which may be unrealistic. Adapting a strategy of Stefanski and Carroll (1987, Biometrika74, 703-716), we propose estimators for the generalized linear model parameters that require no assumptions on the random effects and yield consistent inference regardless of the true distribution. The methods are illustrated via simulation and by application to a study of bone mineral density in women transitioning to menopause.

Duke Scholars

Published In

Biometrics

DOI

ISSN

0006-341X

Publication Date

March 2004

Volume

60

Issue

1

Start / End Page

1 / 7

Location

England

Related Subject Headings

  • Statistics & Probability
  • Progesterone
  • Models, Biological
  • Middle Aged
  • Menopause
  • Longitudinal Studies
  • Logistic Models
  • Linear Models
  • Humans
  • Female
 

Citation

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ICMJE
MLA
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Li, E., Zhang, D., & Davidian, M. (2004). Conditional estimation for generalized linear models when covariates are subject-specific parameters in a mixed model for longitudinal measurements. Biometrics, 60(1), 1–7. https://doi.org/10.1111/j.0006-341X.2004.00170.x
Li, Erning, Daowen Zhang, and Marie Davidian. “Conditional estimation for generalized linear models when covariates are subject-specific parameters in a mixed model for longitudinal measurements.Biometrics 60, no. 1 (March 2004): 1–7. https://doi.org/10.1111/j.0006-341X.2004.00170.x.
Li, Erning, et al. “Conditional estimation for generalized linear models when covariates are subject-specific parameters in a mixed model for longitudinal measurements.Biometrics, vol. 60, no. 1, Mar. 2004, pp. 1–7. Pubmed, doi:10.1111/j.0006-341X.2004.00170.x.
Journal cover image

Published In

Biometrics

DOI

ISSN

0006-341X

Publication Date

March 2004

Volume

60

Issue

1

Start / End Page

1 / 7

Location

England

Related Subject Headings

  • Statistics & Probability
  • Progesterone
  • Models, Biological
  • Middle Aged
  • Menopause
  • Longitudinal Studies
  • Logistic Models
  • Linear Models
  • Humans
  • Female