Adjusting a relative-risk estimate for study imperfections

Journal of Epidemiology and Community Health

Volumn 62, Issue 7, 2008, Pages 655-663

  Maldonado, G ^a  

^a UNIVERSITY OF MINNESOTA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EPIDEMIOLOGY; ESTIMATION METHOD; HEALTH RISK; MEASUREMENT METHOD; NUMERICAL METHOD; QUANTITATIVE ANALYSIS; STATISTICAL ANALYSIS;

ARTICLE; MATHEMATICAL ANALYSIS; QUANTITATIVE ANALYSIS; RISK ASSESSMENT; STATISTICAL ANALYSIS; STATISTICAL MODEL;

ALGORITHMS; BIAS (EPIDEMIOLOGY); EPIDEMIOLOGIC STUDIES; HUMANS; MODELS, STATISTICAL; RESEARCH DESIGN; RISK; STATISTICS AS TOPIC;

EID: 46949084422     PISSN: 0143005X     EISSN: None     Source Type: Journal    
DOI: 10.1136/jech.2007.063909     Document Type: Article

References (40)

1. Robins JM, Greenland S. The role of model selection in causal inference from nonexperimental data. Am J Epidemiol 1986;123:392- 402.
2. Maldonado G, Greenland S. Interpreting model coefficients when the true model form is unknown. Epidemiology 1993;4:310-18.
3. Phillips CV, Maldonado G. Using Monte Carlo methods to quantify the multiple sources of error in studies [abstract]. Am J Epidemiol 1999;149:S17.
4. Phillips CV, LaPole LM. Quantifying errors without random sampling. BMC Med Res Methodol 2003;3:9.
5. Phillips CV. Quantifying and reporting uncertainty from systematic errors. Epidemiology 2003;4:459-66.
6. Lash TL, Silliman RA. A sensitivity analysis to separate bias due to confounding from bias due to predicting misclassification by a variable that does both. Epidemiology 2000;11:544-9.
7. Lash TL, Fink AK. Semi-automated sensitivity analysis to assess systematic errors in observational epidemiologic data. Epidemiology 2003;14:451-8.
8. Greenland S. 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 2003;98:47-54.
9. Greenland S. Interval estimation by simulation as an alternative to and extension of confidence intervals. Int J Epidemiol 2004;33:1389-97.
10. Greenland S. Multiple bias modelling for analysis of observational data [with discussion]. J R Stat Soc [Ser A] 2005;168:267-308.
11. Maldonado G. Quantifying the impact of study imperfections on study results [abstract]. Am J Epidemiol 2005;161:S100.
12. Maldonado G. Informal evaluation of bias may be inadequate [abstract]. Am J Epidemiol 1998;147:S82.
13. Maldonado G, Delzell E, Poole C. A unified approach to conducting and interpreting occupational studies of congenital malformations [abstract]. Am J Epidemiol 1999;149:S59.
14. Maldonado G, Delzell E, Tyl RW, et al. Occupational exposure to glycol ethers and human congenital malformations. Int Arch Occup Environ Hearth 2003;76:405-23.
15. Greenland S. Basic methods for sensitivity analysis of biases. Int J Epidemiol 1996;25:1107-16.
16. Greenland S. Ch. 19. Basic methods for sensitivity analysis and external adjustment. In: Rothman KJ, Greenland S, eds. Modern Epidemiology, 2nd edn. Philadelphia: Lippincott-Raven, 1998:343-57.
17. Maldonado G, Greenland S. Estimating causal effects. Int J Epidemiol 2002;31:422-9.
18. Leamer EE. Sensitivity analyses would help. Am Econ Rev 1985;75:308-13.
19. Eddy DM, Hasselblad V, Schachter R. Meta-analysis by the confidence profile method. New York: Academic Press, 1992.
20. Gustafson P. Measurement error and misclassification in statistics and epidemiology. New York: Chapman and Hall, 2003.
21. Morgan MG, Henrion M. Uncertainty. A guide to dealing with uncertainty in quantitative risk and policy analysis. New York: Cambridge University Press, 1990.
22. Vose D. Risk analysis, a quantitative guide, 2nd edn. New York: John Wiley & Sons, 2000.
23. Greenland S. Sensitivity analysis, Monte-Carlo risk analysis and Bayesian uncertainty assessment. Risk Anal 2001;21:579-83.
24. Fox MP, Lash TL, Greenland S. A method to automate probabilistic sensitivity analyses of misclassified binary variables. Int J Epidemiol 2005;34:1370-6.
25. 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;160:384-92.
26. Greenland S, Gustafson P. Accounting for independent nondifferential misclassification does not increase certainty that an observed association is in the correct direction. Am J Epidemiol 2006;164:63-8.
27. Chu H, Wang Z, Cole SR, et al. Sensitivity analysis of misclassification: a graphical and a Bayesian approach. Ann Epidemiol 2006;16:834-41.
28. Maldonado G, Greenland S. The causal-contrast study design [abstract]. Am J Epidemiol 2000;151:S39.
29. Maldonado G, Greenland S. The intervention-prediction study design [abstract]. Am J Epidemiol 2001;153:S182.
30. Kleinbaum DG, Kupper LL, Morgenstern H. Epidemiologic research: principles and quantitative methods. Belmont: Lifetime Learning Publications, 1982.
31. Greenland S, Criqui MH. Are case-control studies more vulnerable to response bias. Am J Epidemiol 1981;114:175-7.
32. Greenland S, Kleinbaum DG. Correcting for misclassification in two-way tables and matched-pair studies. Int J Epidemiol 1983;1:93-7.
33. Greenland S. Randomization, statistics, and causal inference. Epidemiology 1990;1:421-9.
34. Maldonado G, Greenland S. Simulation study of confounder-selection strategies. Am J Epidemiol 1993;138:923-36.
35. Maldonado G, Greenland S. A comparison of the performance of model-based confidence intervals when the correct model form is unknown: coverage of asymptotic means. Epidemiology 1994;5:171-82.
36. Maldonado G, Greenland S. Impact of model-form selection on the coverage of confidence intervals [abstract]. Am J Epidemiol 1996;143:S24.
37. Maldonado G, Greenland S. Impact of model-form selection on the accuracy of rate estimation. Epidemiology 1996;7:46-54.
38. Maldonado G, Greenland S. Factoring versus linear modeling in rate estimation: a simulation study of relative accuracy. Epidemiology 1998;9:432-5.
39. Greenland S, Maldonado G. The interpretation of multiplicative-model parameters as standardized parameters. Stat Med 1994;13:989-99.
40. Jurek AM, Maldonado G, Greenland S, et al. Exposure-measurement error is frequently ignored when interpreting epidemiologic study results. Eur J Epidemiol 2006;21:871-6.