Bayesian adjustment for covariate measurement errors: A flexible parametric approach

Statistics in Medicine

Volumn 28, Issue 11, 2009, Pages 1580-1600

  Hossain, Shahadut ^a   Gustafson, Paul ^b  

^a BRITISH COLUMBIA CANCER RESEARCH CENTRE   (Canada)

^b UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

Errors in variables; Exposure model; Flexible generalized skew elliptical distributions; MCMC; Measurement errors; Misspecification

Indexed keywords

CHOLESTEROL; LOW DENSITY LIPOPROTEIN CHOLESTEROL;

ARTICLE; BAYES THEOREM; CARDIOVASCULAR RISK; CHOLESTEROL BLOOD LEVEL; CONTROLLED STUDY; COVARIANCE; DATA ANALYSIS; FLEXIBLE GENERALIZED SKEW NORMAL DISTRIBUTION; FLEXIBLE GENERALIZED SKEW T DISTRIBUTION; INTERMETHOD COMPARISON; ISCHEMIC HEART DISEASE; LOGISTIC REGRESSION ANALYSIS; MATHEMATICAL COMPUTING; MATHEMATICAL VARIABLE; MEASUREMENT ERROR; MONTE CARLO METHOD; NONLINEAR REGRESSION ANALYSIS; NORMAL DISTRIBUTION; PARAMETRIC TEST; PROBABILITY; PROCESS MODEL; SENSITIVITY ANALYSIS; STATISTICAL DISTRIBUTION; STATISTICAL MODEL; ALGORITHM; BLOOD; COMPARATIVE STUDY; COMPUTER SIMULATION; CORONARY ARTERY DISEASE; EPIDEMIOLOGY; HUMAN; REGRESSION ANALYSIS; RISK FACTOR; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; BAYES THEOREM; BIAS (EPIDEMIOLOGY); CHOLESTEROL; COMPUTER SIMULATION; CORONARY DISEASE; HUMANS; LIKELIHOOD FUNCTIONS; LINEAR MODELS; MARKOV CHAINS; MONTE CARLO METHOD; NORMAL DISTRIBUTION; REGRESSION ANALYSIS; RISK FACTORS; SENSITIVITY AND SPECIFICITY; STATISTICAL DISTRIBUTIONS;

EID: 67649945924     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.3552     Document Type: Article

References (22)

1. Fuller WA. Measurement Error Models. Wiley: New York, 1987.
2. Carroll RJ, Ruppert D, Stefanski LA. Measurement Error in Nonlinear Models (2nd edn). Chapman & Hall, CRC: London, 2006.
3. Carroll RJ, Stefanski LA. Approximate quasilikelihood estimation in problems with surrogate predictors. Journal of the American Statistical Association 1990; 85:652-663.
4. Cook J, Stefanski LA. A simulation extrapolation method for parametric measurement error models. Journal of the American Statistical Association 1995; 89:1314-1328.
5. Stefanski LA, Carroll RJ. Conditional scores and optimal scores in generalized linear measurement error models. Biometrika 1987; 74:703-716.
6. Nakamura T. Corrected score functions for errors-in-variables models: methodology and application to generalized linear models. Biometrika 1990; 77:127-137.
7. Huang Y, Wang CY. Consistent functional methods for logistic regression with errors in covariates. Journal of the American Statistical Association 2001; 96:1469-1482.
8. Richardson S, Gilks WR. Conditional independence models for epidemiological studies with covariate measurement error. Statistics in Medicine 1993; 12:1703-1722.
9. Gustafson P. Measurement Error and Misclassification in Statistics and Epidemiology: Impacts and Bayesian Adjustments. Chapman and Hall, CRC: London, 2004.
10. Huang X, Stefanski A, Davidian M. Latent-model robustness in structural measurement error models. Biometrika 2006; 93:53-64.
11. Roeder K, Carroll RJ, Lindsay BG. A semi-parametric mixture approach to case-control studies with errors in covariables. Journal of the American Statistical Association 1996; 91:722-732.
12. Richardson S, Leblond L, Jaussent I, Green PJ. Mixture models in measurement error problems with reference to epidemiological studies. Journal of the Royal Statistical Society, Series A 2002; 165:549-566.
13. Bolfarine H, Lachos VH. Skew-probit measurement error models. Statistical Methodology 2007; 4:1-12.
14. Clayton DG. Models for the analysis of cohort and case-control studies with inaccurately measured exposures. In Statistical Models for Longitudinal Studies of Health, Dwyer JH, Feinleib M, Lippert P, Hoffmeister H (eds). Oxford University Press: New York, 1992; 301-331.
15. Richardson S, Gilks WR. A Bayesian approach to measurement error problems in epidemiology using conditional independence models. American Journal of Epidemiology 1993; 138:430-442.
16. Richardson S, Leblond L. Some comments on misspecification of priors in Bayesian modeling of measurement error problems. Statistics in Medicine 1997; 16:203-213.
17. Ma Y, Genton MG, Davidian M. Linear mixed effects models with flexible generalized skew-elliptical random effects. In Skew-Elliptical Distributions and their Applications, Genton MG (ed.). Chapman & Hall, CRC: London, 2004; 339-358.
18. Azzalini A. A class of distributions which includes the normal ones. Scandinavian Journal of Statistics 1985; 12:171-178.
19. Genton MG, Loperfido N. Generalized skew-elliptical distributions and their quadratic forms. Institute of Statistics Mimeo Series 2539, 2002.
20. Ma Y, Genton MG. Flexible class of skew-symmetric distributions. Scandinavian Journal of Statistics 2004; 31:459-468.
21. Genton MG. Skew-symmetric and generalized skew-elliptical distributions. In Skew-Elliptical Distributions and their Applications, Genton MG (ed.). Chapman & Hall, CRC: London, 2004; 81-100.
22. Gelman A. Inference and monitoring convergence. In Markov Chain Monte Carlo in Practice, Gilks W, Richardson S, Spiegelhalter D (eds). Chapman & Hall, CRC: London, 1996; 131-143.