Skip to main content
SpringerLink
Log in

Misclassification

  • Reference work entry
Book cover Handbook of Epidemiology

Abstract

The convention in epidemiology and biostatistics is to divide the study of mismeasured variables into the areas of measurement error for continuous variables and misclassification for categorical variables. Although the topics overlap considerably, chapter Measurement Error of this handbook focuses on measurement error, whereas the present chapter is devoted to misclassification. As a motivating example of a misclassified variable in an epidemiological study, say that a binary exposure is ascertained via subject self-report on a questionnaire. Given human memory limitations, we would usually expect a portion of responses to be erroneous. For instance, in the study of Kraus et al. (1989) on possible association between maternal antibiotic use during pregnancy and sudden infant death syndrome (SIDS), antibiotic use is self-reported by subjects via questionnaire. Examination of medical records of some subjects, however, indicates that the questionnaire responses are erroneous for some subjects. Thus, antibiotic use as determined via questionnaire is subject to misclassification. Moreover, this misclassification has implications when the association between antibiotic use and SIDS is inferred.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 999.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 1,399.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Birkett NJ (1992) Effect of non-differential misclassification on estimates of odds ratios with multiple levels of exposure. Am J Epidemiol 136:356–362

    CAS  PubMed  Google Scholar 

  • Brenner H (1993) Bias due to non-differential misclassification of polytomous confounders. J Clin Epidemiol 46:57–63

    Article  CAS  PubMed  Google Scholar 

  • Brenner H (1996) Correcting for exposure misclassification using an alloyed gold standard. Epidemiology 7:406–410

    Article  CAS  PubMed  Google Scholar 

  • Brenner H, Gefeller O (1993) Use of positive predictive value to correct for disease misclassification in epidemiologic studies. Am J Epidemiol 138:1007–1015

    CAS  PubMed  Google Scholar 

  • Brenner H, Savitz DA, Jöckel KH, Greenland S (1992) Effects of non-differential exposure misclassification in ecologic studies. Am J Epidemiol 135:85–95

    CAS  PubMed  Google Scholar 

  • Broemeling LD (2007) Bayesian biostatistics and diagnostic medicine. Chapman and Hall/CRC, Boca Raton

    Book  Google Scholar 

  • Bross IDJ (1954) Misclassification in 2 × 2 tables. Biometrics 10:478–486

    Article  Google Scholar 

  • Carlin BP, Louis TA (2008) Bayesian methods for data analysis, 3rd edn. Chapman and Hall/CRC, Boca Raton

    Google Scholar 

  • Carroll RJ, Ruppert D, Stefanski LA, Crainiceanu C (2006) Measurement error in nonlinear models, 2nd edn. Chapman and Hall/CRC, Boca Raton

    Book  Google Scholar 

  • Chavance M, Dellatolas G, Lellouch J (1992) Correlated non-differential misclassification of disease and exposure. Int J Epidemiol 21:537–546

    Article  CAS  PubMed  Google Scholar 

  • Chu H, Cole SR, Wei Y, Ibrahim JG (2009) Estimation and inference for case-control studies with multiple non-gold standard exposure assessments: with an occupational health application. Biostatistics 10:591–602

    Article  PubMed Central  PubMed  Google Scholar 

  • Chu R, Gustafson P, Le N (2010) Bayesian adjustment for exposure misclassification in case-control studies. Stat Med 29:994–1003

    PubMed  Google Scholar 

  • Cole SR, Chu H, Greenland S (2006) Multiple-imputation for measurement error correction (with comment). Int J Epidemiol 35:1074–1082

    Article  PubMed  Google Scholar 

  • Cook J, Stefanski LA (1995) A simulation extrapolation method for parametric measurement error models. J Am Stat Assoc 89:1314–1328

    Article  Google Scholar 

  • Dendukuri N, Joseph L (2001) Bayesian approaches to modeling the conditional dependence between multiple diagnostic tests. Biometrics 57:158–167

    Article  CAS  PubMed  Google Scholar 

  • Dosemeci M, Wacholder S, Lubin JH (1990) Does non-differential misclassification of exposure always bias a true effect toward the null value? Am J Epidemiol 132:746–748

    CAS  PubMed  Google Scholar 

  • Drews C, Greenland S (1990) The impact of differential recall on the results of case-control studies. Int J Epidemiol 19:1107–1112

    Article  CAS  PubMed  Google Scholar 

  • Fewell Z, Davey Smith G, Sterne J (2007) The impact of residual and unmeasured confounding in epidemiologic studies: a simulation study. Am J Epidemiol 166:646–655

    Article  PubMed  Google Scholar 

  • Flegal KM, Keyl PM, Nieto FJ (1991) Differential misclassification arising from non-differential errors in exposure measurement. Am J Epidemiol 134:1233–1244

    CAS  PubMed  Google Scholar 

  • Greenland S (1980) The effect of misclassification in the presence of covariates. Am J Epidemiol 112:564–569

    CAS  PubMed  Google Scholar 

  • Greenland S (1982) The effect of misclassification in matched-pair case-control studies. Am J Epidemiol 116:402–406

    CAS  PubMed  Google Scholar 

  • Greenland S (1988) Statistical uncertainty due to misclassification: implications for validation substudies. J Clin Epidemiol 41:1167–1176

    Article  CAS  PubMed  Google Scholar 

  • Greenland S (2001) Sensitivity analysis, Monte Carlo risk analysis, and Bayesian uncertainty assessment. Risk Anal 21:579–583

    Article  CAS  PubMed  Google Scholar 

  • Greenland S (2003) The impact of prior distributions for uncontrolled confounding and response bias: a case study of the relation of wire codes and magnetic fields to childhood leukemia. J Am Stat Assoc 97:47–54

    Article  Google Scholar 

  • Greenland S (2005) Multiple bias modeling for analysis of observational data (with discussion). J R Stat Soc Ser A 168:267–308

    Article  Google Scholar 

  • Greenland S (2008) Maximum-likelihood and closed-form estimators of epidemiologic measures under misclassification. J Stat Plan Inference 138:528–538

    Article  Google Scholar 

  • Greenland S (2009a) Bayesian perspectives for epidemiologic research. III. Bias analysis via missing-data methods. Int J Epidemiol 38:1662–1673. doi: 10.1093/ije/dyp278

    Article  PubMed  Google Scholar 

  • Greenland S (2009b) Relaxation priors and penalties for plausible modeling of nonidentified bias sources. Stat Sci 24:195–210

    Article  Google Scholar 

  • Greenland S, Gustafson P (2006) Accounting for independent non-differential misclassification does not increase certainty than an observed association is in the correct direction. Am J Epidemiol 164:63–68

    Article  PubMed  Google Scholar 

  • Greenland S, Kleinbaum DG (1983) Correcting for misclassification in two-way tables and matched-pair studies. Int J Epidemiol 12:93–97

    Article  CAS  PubMed  Google Scholar 

  • Greenland S, Lash TL (2008) Bias analysis. Chapter 19. In: Rothman KJ, Greenland S, Lash TL (eds) Modern epidemiology, 3rd edn. Lippincott-Wolters-Kluwer, Philadelphia, pp 345–380

    Google Scholar 

  • Gustafson P (2003) Measurement error and misclassification in statistics and epidemiology: impacts and Bayesian adjustments. Chapman and Hall/CRC, Boca Raton

    Book  Google Scholar 

  • Gustafson P (2009) What are the limits of posterior distributions arising from nonidentified models, and why should we care? J Am Stat Assoc 104:1682–1695

    Article  Google Scholar 

  • Gustafson P, Greenland S (2006) Curious phenomena in adjusting for exposure misclassification. Stat Med 25:87–103

    Article  PubMed  Google Scholar 

  • Gustafson P, Le ND (2002) Comparing the effects of continuous and discrete covariate measurement error with emphasis on dichotomization of mismeasured predictors. Biometrics 28:878–887

    Article  Google Scholar 

  • Gustafson P, Le ND, Saskin R (2001) Case-control analysis with partial knowledge of exposure misclassification probabilities. Biometrics 57:598–609

    Article  CAS  PubMed  Google Scholar 

  • Hanson TE, Johnson WO, Gardner IA, Georgiadis MP (2003) Determining the infection status of a herd. J Agric Biol Environ Stat 8:469–485

    Article  Google Scholar 

  • Hui SL, Walter SD (1980) Estimating the error rates of diagnostic tests. Biometrics 36:167–171

    Article  CAS  PubMed  Google Scholar 

  • Jones G, Johnson WO, Hanson TE, Christensen R (2010) Identifiability of models for multiple diagnostic testing in the absence of a gold standard. Biometrics 66:855–863

    Article  PubMed  Google Scholar 

  • Kraus JF, Greenland S, Bulterys M (1989) Risk factors for sudden infant death syndrome in the U.S. collaborative perinatal project. Int J Epidemiol 18:113–120

    Article  CAS  PubMed  Google Scholar 

  • Kristensen P (1992) Bias from non-differential but dependent misclassification of exposure and outcome. Epidemiology 3:210–215

    Article  CAS  PubMed  Google Scholar 

  • Küchenhoff H, Mwalili SM, Lesaffre E (2006) A general method for dealing with misclassification in regression: the misclassification SIMEX. Biometrics 62:85–96

    Article  PubMed  Google Scholar 

  • Lash TL, Fox MP, Fink AK (2009) Applying quantitative bias analysis to epidemiologic data. Springer, New York

    Book  Google Scholar 

  • Little RJA, Rubin DB (2002) Statistical analysis with missing data, 2nd edn. Wiley, New York

    Google Scholar 

  • Lyles RH (2002) A note on estimating crude odds ratios in case-control studies with differentially misclassified exposure. Biometrics 58:1034–1037

    Article  PubMed  Google Scholar 

  • Marshall JR (1990) Validation study methods for estimating exposure proportions and odds ratios with misclassified data. J Clin Epidemiol 43:941–947

    Article  CAS  PubMed  Google Scholar 

  • Marshall JR, Hastrup JL, Ross JS (1999) Mismeasurement and the resonance of strong confounders: correlated errors. Am J Epidemiol 150:88–96

    Article  CAS  PubMed  Google Scholar 

  • Natarajan L (2009) Regression calibration for dichotomized mismeasured predictors. Int J Biostat 5(1):Article 12

    Google Scholar 

  • Neuhaus JM (1999) Bias and efficiency loss due to misclassified responses in binary regression. Biometrika 86:843–855

    Article  Google Scholar 

  • Newell DJ (1962) Errors in interpretation of errors in epidemiology. Am J Public Health 52: 1925–1928

    Article  CAS  Google Scholar 

  • Pepe MS (2003) The statistical evaluation of medical tests for classification and prediction. Oxford University Press, Oxford

    Google Scholar 

  • Savitz DA, Baron AE (1989) Estimating and correcting for confounder misclassification. Am J Epidemiol 129:1062–1071

    CAS  PubMed  Google Scholar 

  • Tu X, Litvak E, Pagano M (1994) Studies of AIDS and HIV surveillance screening tests: can we get more by doing less? Stat Med 13:1905–1919

    Article  CAS  PubMed  Google Scholar 

  • Tu X, Litvak E, Pagano M (1995) On the informativeness and accuracy of pooled testing in estimating prevalence of a rare disease: application in HIV screening. Biometrika 82:287–297

    Article  Google Scholar 

  • Wacholder S, Armstrong B, Hartge P (1993) Validation studies using an alloyed gold standard. Am J Epidemiol 137:1251–1258

    CAS  PubMed  Google Scholar 

  • Wacholder S, Dosemeci M, Lubin JH (1991) Blind assignment of exposure does not prevent differential misclassification. Am J Epidemiol 134:433–437

    CAS  PubMed  Google Scholar 

  • Walker AM, Blettner M (1985) Comparing imperfect measures of exposure. Am J Epidemiol 121:783–790

    CAS  PubMed  Google Scholar 

  • Weinberg CR, Umbach DM, Greenland S (1994) When will non-differential misclassification of an exposure preserve the direction of a trend? (with discussion). Am J Epidemiol 140:565–571

    CAS  PubMed  Google Scholar 

  • Zhou XH, Obuchowski NA, McClish DK (2002) Statistical methods in diagnostic medicine. Wiley, New York

    Book  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Statistics, University of British Columbia, 6356 Agricultural Road, Room 333, BC V6T 1Z2, Vancouver, BC, Canada

    Paul Gustafson

  2. Department of Epidemiology, School of Public Health, University of California, 90095-1772, Los Angeles, CA, USA

    Sander Greenland

Authors
  1. Paul Gustafson
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sander Greenland
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Epidemiological Methods and Etiologic Research, Leibniz Institute for Prevention Research and Epidemiology – BIPS, Bremen, Germany

    Wolfgang Ahrens

  2. Department of Biometry and Data Management, Leibniz Institute for Prevention Research and Epidemiology – BIPS, Bremen, Germany

    Iris Pigeot

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer Science+Business Media New York

About this entry

Cite this entry

Gustafson, P., Greenland, S. (2014). Misclassification. In: Ahrens, W., Pigeot, I. (eds) Handbook of Epidemiology. Springer, New York, NY. https://doi.org/10.1007/978-0-387-09834-0_58

Download citation

  • DOI: https://doi.org/10.1007/978-0-387-09834-0_58

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-09833-3

  • Online ISBN: 978-0-387-09834-0

  • eBook Packages: MedicineReference Module Medicine

Publish with us

Policies and ethics

Search

Navigation