Sensitivity analysis for misclassification in logistic regression via likelihood methods and predictive value weighting

Statistics in Medicine

Volumn 29, Issue 22, 2010, Pages 2297-2309

  Lyles, Robert H ^a   Lin, Ji ^a  

^a EMORY UNIVERSITY   (United States)

Author keywords

Bias; Errors in variables; Odds ratio; Regression

Indexed keywords

ARTICLE; COMPUTER PROGRAM; LOGISTIC REGRESSION ANALYSIS; PREDICTIVE VALIDITY; SENSITIVITY ANALYSIS; SENSITIVITY AND SPECIFICITY; VALIDITY;

ANTI-BACTERIAL AGENTS; CASE-CONTROL STUDIES; COMPUTER SIMULATION; FEMALE; HUMANS; INFANT; LOGISTIC MODELS; MATERNAL EXPOSURE; SUDDEN INFANT DEATH;

EID: 77956895720     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.3971     Document Type: Article

References (33)

1. Carroll RJ, Ruppert D, Stefanski LA, Crainiceanu CM. Measurement Error in Nonlinear Models (2nd edn). Chapman & Hall: New York, 2006.
2. Bross IDJ. Misclassification in 2 x 2 tables. Biometrics 1954; 10:478-486.
3. Barron BA. The effects of misclassification on the estimation of relative risk. Biometrics 1977; 33:414-418.
4. Greeenland S, Kleinbaum D. Correcting for misclassification in two-way tables and matched-pair studies. International Journal of Epidemiology 1983; 12:93-97.
5. Greenland S. Variance estimation for epidemiologic effect estimates under misclassification. Statistics in Medicine 1987; 7:745-757.
6. Marshall RJ. Validation study methods for estimating proportions and odds ratios with misclassified data. Journal of Clinical Epidemiology 1990; 43:941-947.
7. Morrissey MJ, Spiegelman D. Matrix methods for estimating odds ratios with misclassified exposure data: extensions and comparisons. Biometrics 1999; 55:338-344.
8. Rindskopf D, Rindskopf W. The value of latent class analysis in medical diagnosis. Statistics in Medicine 1986; 5:21-27.
9. Liu X, Liang K-Y. Adjustment for nondifferential misclassification error in the generalized linear model. Statistics in Medicine 1991; 10:1197-1211.
10. Lash TL, Fink AK. Semi-automated sensitivity analysis to assess systematic errors in observational data. Epidemiology 2003; 14:451-458.
11. Fox MP, Lash TL, Greenland S. A method to automate probabilistic sensitivity analyses of misclassified binary variables. International Journal of Epidemiology 2005; 34:1370-1376.
12. Chu H, Wang Z, Cole SR, Greenland S. Sensitivity analysis of misclassification: a graphical and a Bayesian approach. Annals of Epidemiology 2006; 16:834-841.
13. Orsini N, Bellocco R, Bottai M, Wolk A, Greenland S. A tool for deterministic and probabilistic sensitivity analysis of epidemiologic studies. Stata Journal 2008; 8:29-48.
14. Gustafson P, Le ND, Saskin R. Case-control analysis with partial knowledge of exposure misclassification probabilities. Biometrics 2001; 57:598-609.
15. Magder LS, Hughes JP. Logistic regression when the outcome is measured with uncertainty. American Journal of Epidemiology 1997; 146:195-203.
16. Drews CD, Kraus JF, Greenland S. Recall bias in a case-control study of sudden infant death syndrome. International Journal of Epidemiology 1990; 19:405-411. (Pubitemid 20197584)
17. Thomas D, Stram D, Dwyer J. Exposure measurement error: influence on exposure-disease relationships and methods of correction. Annual Reviews of Public Health 1993; 14:69-93.
18. Lyles RH. A note on estimating crude odds ratios in case-control studies with differentially misclassified exposure. Biometrics 2002; 58:1034-1037.
19. Greenland S. Maximum-likelihood and closed-form estimators of epidemiologic measures under misclassification. Journal of Statistical Planning and Inference 2008; 138:528-538.
20. SAS Institute, Inc. SAS/STAT 9.1 User's Guide, vol. 4. SAS Institute: Cary, NC, 2004.
21. Efron B, Tibshirani RJ. An Introduction to the Bootstrap. Chapman & Hall: New York, 1993.
22. Hinkley D. Jackknife methods. In Encyclopedia of Statistical Sciences, Kotz S, Johnson NL (eds), vol. 4, Wiley: New York, 1983; 280-287.
23. Neuhaus JM. Bias and efficiency loss due to misclassified responses in logistic regression. Biometrika 1999; 86:843-855.
24. Neuhaus JM. Analysis of clustered and longitudinal binary data subject to response misclassification. Biometrics 2002; 58:675-683.
25. SAS Institute, Inc. SAS IML 9.1 User's Guide. SAS Institute: Cary, NC, 2004.
26. Venables WN, Ripley BD. Modern Applied Statistics with S-Plus. Springer: New York, 1994.
27. Everitt BS, Hothorn T. A Handbook of Statistical Analyses Using R. Chapman & Hall: New York, 2006.
28. Hosmer DW, Lemeshow S. Applied Logistic Regression (2nd edn). Wiley: New York, 2000.
29. Fleiss JL, Levin B, Paik MC. Statistical Methods for Rates and Proportions (3rd edn). Wiley: New York, 2003.
30. Lipsitz SR, Ibrahim JG. A conditional model for incomplete covariates in parametric regression models. Biometrika 1996; 83:916-922.
31. Lyles RH, Lin H-M, Williamson JM. A practical approach to computing power for generalized linear models with nominal, count, or ordinal responses. Statistics in Medicine 2007; 26:1632-1648.
32. Hlatky M, Pryor D, Harrell F, Califf R, Mark D, Rosati R. Factors affecting sensitivity and specificity of exercise electrocardiography: multivariable analysis. The American Journal of Medicine 1984; 77:64-71.
33. Karakaya J, Aksoy D, Harmanci A, Karaagaoglu E, Gurlek A. Predictive ability of fasting plasma glucose for a diabetic 2-h postload glucose value in oral glucose tolerance test: spectrum effect. Journal of Diabetes and Its Complications 2007; 21:300-305.