Efficacy of repeated measures in regression models with measurement error

X. Liu, K. Y. Liang

Research output: Contribution to journalArticle

Abstract

Ignoring measurement error may cause bias in the estimation of regression parameters. When the true covariates are unobservable, multiple imprecise measurements can be used in the analysis to correct for the associated bias. We suggest a simple estimating procedure that gives consistent estimates of regression parameters by using the repeated measurements with error. The relative Pitman efficiency of our estimator based on models with and without measurement error has been found to be a simple function of the number of replicates and the ratio of intra- to inter-variance of the true covariate. The procedure thus provides a guide for deciding the number of repeated measurements in the design stage. An example from a survey study is presented.

Original languageEnglish (US)
Pages (from-to)645-654
Number of pages10
JournalBiometrics
Volume48
Issue number2
DOIs
StatePublished - 1992

Fingerprint

Repeated Measurements
Repeated Measures
Measurement errors
Measurement Error
Efficacy
Covariates
Regression Model
Regression
Pitman Efficiency
Consistent Estimates
Relative Efficiency
Estimator
Model
Design
Surveys and Questionnaires

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Public Health, Environmental and Occupational Health
  • Agricultural and Biological Sciences (miscellaneous)
  • Applied Mathematics
  • Statistics and Probability

Cite this

Efficacy of repeated measures in regression models with measurement error. / Liu, X.; Liang, K. Y.

In: Biometrics, Vol. 48, No. 2, 1992, p. 645-654.

Research output: Contribution to journalArticle

Liu, X. ; Liang, K. Y. / Efficacy of repeated measures in regression models with measurement error. In: Biometrics. 1992 ; Vol. 48, No. 2. pp. 645-654.
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