Adjusting for outcome misclassification: The importance of accounting for case-control sampling and other forms of outcome-related selection

Annals of Epidemiology

Volumn 23, Issue 3, 2013, Pages 129-135

  Jurek, Anne M ^a,b   Maldonado, George ^b   Greenland, Sander ^c  

^a Allina Health   (United States)

^b UNIVERSITY OF MINNESOTA   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Bias; Birth certificates; Case control studies; Outcome misclassification; Predictive values; Sampling; Sensitivity and specificity

Indexed keywords

ANALYTICAL ERROR; ARTICLE; CASE CONTROL STUDY; CLASSIFICATION; CLEFT LIP; CLEFT PALATE; COHORT ANALYSIS; FEMALE; HEALTH SURVEY; HUMAN; MATERNAL SMOKING; OUTCOME ASSESSMENT; PREGNANCY; PREGNANT WOMAN; PRIORITY JOURNAL; RISK ASSESSMENT; SAMPLING; SENSITIVITY AND SPECIFICITY;

BIRTH CERTIFICATES; CASE-CONTROL STUDIES; CLEFT LIP; CLEFT PALATE; DATA INTERPRETATION, STATISTICAL; FEMALE; HUMANS; PREGNANCY; PREGNANCY COMPLICATIONS; PREGNANCY OUTCOME; PRENATAL EXPOSURE DELAYED EFFECTS; RESEARCH DESIGN; SELECTION BIAS; SMOKING;

EID: 84873474442     PISSN: 10472797     EISSN: 18732585     Source Type: Journal    
DOI: 10.1016/j.annepidem.2012.12.007     Document Type: Article

References (30)

1. Greenland S., Kleinbaum D. Correcting for misclassification in two-way tables and matched-pair studies. Int J Epidemiol 1983, 12(1):93-97.
2. Maldonado G. Informal evaluation of bias may be inadequate. Am J Epidemiol 1998, 147:S82. [abstract].
3. Phillips C., Maldonado G. Using Monte Carlo methods to quantify the multiple sources of error in studies. Am J Epidemiol 1999, 149:S17. [abstract].
4. Phillips C., LaPole L. Quantifying errors without random sampling. BMC Med Res Methodol 2003, 3(9). 10.1186/1471-2288-3-9.
5. Phillips C. Quantifying and reporting uncertainty from systematic errors. Epidemiology 2003, 14(4):459-466.
6. Gustafson P. Measurement error and misclassification in statistics and epidemiology 2003, Chapman and Hall, Boca Raton, FL.
7. Maldonado G. Quantifying the impact of study imperfections on study results. Am J Epidemiol 2005, 161:S100. [abstract].
8. Greenland S. Multiple bias modelling for analysis of observational data. J R Stat Soc [Ser A] 2005, 168(2):267-306. [with discussion].
9. Fox M.P., Lash T.L., Greenland S. A method to automate probabilistic sensitivity analyses of misclassified binary variables. Int J Epidemiol 2005, 34(6):1370-1376.
10. Greenland S., Lash T.L. Bias analysis [Ch. 19]. Modern epidemiology 2008, Lippincott Williams & Wilkins, Philadelphia, p. 345-80. 3rd ed. K.J. Rothman, S. Greenland, T.L. Lash (Eds.).
11. Maldonado G. Adjusting a relative-risk estimate for study imperfections. J Epidemiol Community Health 2008, 62(7):655-663.
12. Lash T.L., Fox M.P., Fink A.K. Applying quantitative bias analysis to epidemiologic data 2009, Springer, Dordrecht.
13. Greenland S. Bayesian perspectives for epidemiologic research: III. Bias analysis via missing-data methods. Int J Epidemiol 2009, 38(6):1662-1673. Corrigendum (2010) International Journal of Epidemiology 39(4), 1116.
14. Greenland S., Rothman K.J. Measures of occurrence [Ch. 3]. Modern epidemiology 2008, Lippincott Williams & Wilkins, Philadelphia, p. 32-50. 3rd ed. K.J. Rothman, S. Greenland, T.L. Lash (Eds.).
15. Wyszynski D.F., Wu T. Use of US birth certificate data to estimate the risk of maternal cigarette smoking for oral clefting. Cleft Palate Craniofac J 2002, 39(2):188-192.
16. Kirby R.S. The quality of vital perinatal statistics data, with special reference to prenatal care. Paediatr Perinat Epidemiol 1997, 11(1):122-128.
17. Kirby R.S. The quality of data reported on birth certificates. Am J Public Health 1997, 87(2):301. [letter].
18. Kirby R.S. Birth certificates are an inappropriate source for identifying cases of birth defects in epidemiologic studies. Int J Circumpolar Health 2007, 66(1):4.
19. Watkins M.L., Edmonds L., McClearn A., Mullins L., Mulinare J., Khoury M. The surveillance of birth defects: the usefulness of the revised US standard birth certificate. Am J Public Health 1996, 86(5):731-734.
20. Piper J.M., Mitchel E.F., Snowden M., Hall C., Adams M., Taylor P. Validation of 1989 Tennessee birth certificates using maternal and newborn hospital records. Am J Epidemiol 1993, 137(7):758-768.
21. Jurek A.M., Lash T.L., Maldonado G. Specifying exposure classification parameters for sensitivity analysis: family breast cancer history. Clin Epidemiol 2009, 1:109-117.
22. Lyles R. A note on estimating crude odds ratios in case-control studies with differentially misclassified exposure (with discussion). Biometrics 2002, 58(4):1034-1037.
23. Greenland S. Maximum-likelihood and closed-form estimators of epidemiologic measures under misclassification. J Stat Plan Inference 2008, 138(2):528-538.
24. Carroll R.J., Ruppert D., Stefanski L.A., Crainiceanu C. Measurement error in nonlinear models: a modern perspective 2006, Chapman & Hall, Boca Raton, FL. 2nd ed.
25. Brenner H., Savitz D.A. The effects of sensitivity and specificity of case selection on validity, sample size, precision, and power in hospital-based case-control studies. Am J Epidemiol 1990, 132(1):181-192.
26. Lyles R., Allen A. Estimating crude or common odds ratios in case-control studies with informatively missing exposure data. Am J Epidemiol 2002, 155(3):274-281.
27. Steenland K., Greenland S. Monte-Carlo sensitivity analysis and Bayesian analysis of smoking as an unmeasured confounder in a study of silica and lung cancer. Am J Epidemiol 2004, 160(4):384-392.
28. Lash T.L. Bias analysis applied to Agricultural Health Study publications to estimate non-random sources of uncertainty. J Occup Med Toxicol 2007, 2(15). 10.1186/1745-6673-2-15.
29. MacLehose R.F., Gustafson P. Is probabilistic bias analysis approximately Bayesian?. Epidemiology 2012, 23(1):151-158.
30. Cole S.R., Chu H., Greenland S. Multiple-imputation for measurement-error correction. Int J Epidemiol 2006, 35(4):1074-1081.