The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
A method to automate probabilistic sensitivity analyses of misclassified binary variables
Abstract
BACKGROUND: Misclassification bias is present in most studies, yet uncertainty about its magnitude or direction is rarely quantified. METHODS: The authors present a method for probabilistic sensitivity analysis to quantify likely effects of misclassification of a dichotomous outcome, exposure or covariate. This method involves reconstructing the data that would have been observed had the misclassified variable been correctly classified, given the sensitivity and specificity of classification. The accompanying SAS macro implements the method and allows users to specify ranges of sensitivity and specificity of misclassification parameters to yield simulation intervals that incorporate both systematic and random error. RESULTS: The authors illustrate the method and the accompanying SAS macro code by applying it to a study of the relation between occupational resin exposure and lung-cancer deaths. The authors compare the results using this method with the conventional result, which accounts for random error only, and with the original sensitivity analysis results. CONCLUSION: By accounting for plausible degrees of misclassification, investigators can present study results in a way that incorporates uncertainty about the bias due to misclassification, and so avoid misleadingly precise-looking results.
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Citations
Cites
Statistical Analysis with Missing Data
Little, R. J. A., & Rubin, D. B. (2002) · Wiley Series in Probability and Statistics · doi:10.1002/9781119013563 · Cited by 8,473
Multiple-bias modelling for analysis of observational data
Greenland, S. (2005) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/j.1467-985x.2004.00349.x · Cited by 497
THE EFFECT OF MISCLASSIFICATION IN THE PRESENCE OF COVARIATES
GREENLAND, S. (1980) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a113025 · Cited by 494
Self-citationRandomization, Statistics, and Causal Inference
Greenland, S. (1990) · Epidemiology · doi:10.1097/00001648-199011000-00003 · Cited by 385
Self-citationQuantifying and Reporting Uncertainty from Systematic Errors
Phillips, C. V. (2003) · Epidemiology · doi:10.1097/01.ede.0000072106.65262.ae · Cited by 168
Greenland, S. (2003) · Journal of the American Statistical Association · doi:10.1198/01621450338861905 · Cited by 141
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Cited by
Multiple-bias modelling for analysis of observational data
Greenland, S. (2005) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/j.1467-985x.2004.00349.x · Cited by 497
Shi, L., Steenland, K., Li, H., Liu, P., Zhang, Y., Lyles, R. H., Requia, W. J., Ilango, S. D., Chang, H. H., Wingo, T., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-27049-2 · Cited by 239
Shi, L., Zhu, Q., Wang, Y., Hao, H., Zhang, H., Schwartz, J., Amini, H., van Donkelaar, A., Martin, R. V., Steenland, K., et al. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2211282119 · Cited by 145
On the need for quantitative bias analysis in the peer-review process
Fox, M. P., & Lash, T. L. (2017) · American Journal of Epidemiology · doi:10.1093/aje/kwx057 · Cited by 31
Self-citationDesai, R. J., Levin, R., Lin, K. J., & Patorno, E. (2020) · Journal of the American Heart Association · doi:10.1161/jaha.120.016906 · Cited by 29
Invited Commentary: Dealing With the Inevitable Deficiencies of Bias Analysis—and All Analyses
Greenland, S. (2021) · American Journal of Epidemiology · doi:10.1093/aje/kwab069 · Cited by 22
Self-citationWang, H., Li, F., Miao, M., Yu, Y., Ji, H., Liu, H., Huang, R., Obel, C., Zhang, J., & Li, J. (2020) · Human Reproduction · doi:10.1093/humrep/deaa035 · Cited by 19
Wang, X., Lee, N. L., & Burstyn, I. (2020) · Annals of Epidemiology · doi:10.1016/j.annepidem.2020.01.001 · Cited by 6
Fisher, S. C., Romitti, P. A., Tracy, M., Howley, M. M., Jabs, E. W., Browne, M. L., & Study, T. N. B. D. P. (2024) · Birth Defects Research · doi:10.1002/bdr2.2420 · Cited by 2
Metadata
- Authors
- Fox, M. P., Lash, T. L., & Greenland, S.
- Venue
- International Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 2005-09-19
- Volume
- 34
- Issue
- 6
- Pages
- 1370-1376
- ISSN
- 0300-5771 (ISSN-L)
- 1464-3685
- OpenAlex
- W2146655274
- Cited by
- 288
- References
- 6
- FWCI
- 9.36
- Type
- journal article
- Language
- en
- Open access
- closed
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