Multiple-bias modelling for analysis of observational data
Abstract
Summary Conventional analytic results do not reflect any source of uncertainty other than random error, and as a result readers must rely on informal judgments regarding the effect of possible biases. When standard errors are small these judgments often fail to capture sources of uncertainty and their interactions adequately. Multiple-bias models provide alternatives that allow one systematically to integrate major sources of uncertainty, and thus to provide better input to research planning and policy analysis. Typically, the bias parameters in the model are not identified by the analysis data and so the results depend completely on priors for those parameters. A Bayesian analysis is then natural, but several alternatives based on sensitivity analysis have appeared in the risk assessment and epidemiologic literature. Under some circumstances these methods approximate a Bayesian analysis and can be modified to do so even better. These points are illustrated with a pooled analysis of case–control studies of residential magnetic field exposure and childhood leukaemia, which highlights the diminishing value of conventional studies conducted after the early 1990s. It is argued that multiple-bias modelling should become part of the core training of anyone who will be entrusted with the analysis of observational data, and should become standard procedure when random error is not the only important source of uncertainty (as in meta-analysis and pooled analysis).
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Monte Carlo sensitivity analyses were used to quantify the uncertainty in observed risk estimates due to the simultaneous operation of unmeasured confounders, selection bias differential with respect to both personality/SES and mortality, and systematic measurement error in personality and SES.
“Finally, we used Monte Carlo sensitivity analyses (MCSA) (39,40) to quantify the uncertainty in observed risk estimates due to the simultaneous operation of unmeasured confounders, selection bias differential with respect to both personality/SES and mortality, and systematic measurement error in personality and SES.”
From Personality, Socioeconomic Status, and All-Cause Mortality in the United States (2010) · cites this paper as [40]
Cites
An Introduction to the Bootstrap
Efron, B., & Tibshirani, R. J. (1994) · doi:10.1201/9780429246593 · Cited by 40,500 · see citing works
Sample Selection Bias as a Specification Error
Heckman, J. J. (1979) · Econometrica · doi:10.2307/1912352 · Cited by 28,779 · see citing works
Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013) · doi:10.1201/b16018 · Cited by 27,276 · see citing works
An Introduction to the Bootstrap
Efron, B., & Tibshirani, R. J. (1993) · doi:10.1007/978-1-4899-4541-9 · Cited by 21,230 · see citing works
Statistical Analysis With Missing Data
Lahiff, M., Little, R. J. A., & Rubin, D. B. (1989) · Journal of the American Statistical Association · doi:10.2307/2289883 · Cited by 17,384 · see citing works
RUBIN, D. B. (1976) · Biometrika · doi:10.1093/biomet/63.3.581 · Cited by 9,925 · see citing works
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 · see citing works
Davey Smith, G., & Ebrahim, S. (2003) · International Journal of Epidemiology · doi:10.1093/ije/dyg070 · Cited by 5,882 · see citing works
Discrete Multivariate Analysis: Theory and Practice.
Beniger, J. R., Bishop, Y. M. M., Feinberg, S. E., Holland, P. W., Light, R. J., & Mosteller, F. C. (1975) · Contemporary Sociology A Journal of Reviews · doi:10.2307/2063625 · Cited by 5,119 · see citing works
Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author)
Breiman, L. (2001) · Statistical Science · doi:10.1214/ss/1009213726 · Cited by 4,340 · see citing works
Identification of Causal Effects Using Instrumental Variables
Angrist, J. D., Imbens, G. W., & Rubin, D. B. (1996) · Journal of the American Statistical Association · doi:10.1080/01621459.1996.10476902 · Cited by 4,230 · see citing works
Bayesian Inference in Statistical Analysis.
Kadane, J. B., Box, G. E. P., & Tiao, G. C. (1975) · Journal of the American Statistical Association · doi:10.2307/2285412 · Cited by 3,869 · see citing works
Causal Diagrams for Epidemiologic Research
Greenland, S., Pearl, J., & Robins, J. M. (1999) · Epidemiology · doi:10.1097/00001648-199901000-00008 · Cited by 3,728 · see citing works
Air Pollution and Hospital Admissions for Heart Disease in Eight U.S. Counties
Schwartz, J. D. (1999) · Epidemiology · doi:10.1097/00001648-199901000-00005 · Cited by 3,043 · see citing works
Bayesian Data Analysis, 2nd edn
Brix, A. (2005) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/j.1467-985x.2004.00347_4.x · Cited by 2,588 · see citing works
Bayesian inference for causal effects: The role of randomization
Rubin, D. B. (1978) · The Annals of Statistics · doi:10.1214/aos/1176344064 · Cited by 2,503 · see citing works
Rosenbaum, P. R. (2002) · Springer series in statistics · doi:10.1007/978-1-4757-3692-2 · Cited by 2,414 · see citing works
Box, G. E. P. (1976) · Journal of the American Statistical Association · doi:10.1080/01621459.1976.10480949 · Cited by 2,372 · see citing works
Limitations of the Application of Fourfold Table Analysis to Hospital Data
Berkson, J. (1946) · Biometrics Bulletin · doi:10.2307/3002000 · Cited by 1,810 · see citing works
Maternal Pesticide Exposure from Multiple Sources and Selected Congenital Anomalies
Shaw, G. M., Wasserman, C. R., O’Malley, C. D., Nelson, V. E., & Jackson, R. J. (1999) · Epidemiology · doi:10.1097/00001648-199901000-00011 · Cited by 1,783 · see citing works
Discrete Multivariate Analysis
(1977) · Technometrics · doi:10.1080/00401706.1977.10489605 · Cited by 1,773 · see citing works
Morgan, M. G., & Henrion, M. (1990) · Cambridge University Press eBooks · doi:10.1017/cbo9780511840609 · Cited by 1,711 · see citing works
Holder, R. L., Mosteller, F. C., & Tukey, J. W. (1979) · Journal of the Royal Statistical Society Series C (Applied Statistics) · doi:10.2307/2346739 · Cited by 1,686 · see citing works
Stampfer, M. J., & Colditz, G. A. (1991) · Preventive Medicine · doi:10.1016/0091-7435(91)90006-p · Cited by 1,611 · see citing works
Can dietary beta-carotene materially reduce human cancer rates?
Peto, R., Doll, R., Buckley, J. D., & Sporn, M. B. (1981) · Nature · doi:10.1038/290201a0 · Cited by 1,563 · see citing works
Principal Stratification in Causal Inference
Frangakis, C., & Rubin, D. B. (2002) · Biometrics · doi:10.1111/j.0006-341x.2002.00021.x · Cited by 1,496 · see citing works
Osborn, J. F., Mosteller, F. C., & Tukey, J. W. (1978) · Journal of the Royal Statistical Society Series A (General) · doi:10.2307/2344493 · Cited by 1,465 · see citing works
Bayesian Statistics without Tears: A Sampling-Resampling Perspective
Smith, A. F. M., & Gelfand, A. E. (1992) · The American Statistician · doi:10.1080/00031305.1992.10475856 · Cited by 1,005 · see citing works
Bayesian Inference in Statistical Analysis
Gokhale, D. V., Box, G. E. P., & Tiao, G. C. (1974) · Biometrics · doi:10.2307/2529631 · Cited by 1,000 · see citing works
Inference and disputed authorship : The Federalist
Mosteller, F. C., & Wallace, D. K. (1964) · Medical Entomology and Zoology · Cited by 916 · see citing works
Smoking and Lung Cancer: Recent Evidence and a Discussion of Some Questions
Cornfield, J., Haenszel, W. M., Hammond, E., Lilienfeld, A. M., Shimkin, M. B., & Wynder, E. L. (1959) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/22.1.173 · Cited by 841 · see citing works
NONPARAMETRIC BOUNDS ON TREATMENT EFFECTS
Manski, C. F. (1989) · American Economic Review · Cited by 801 · see citing works
Overweight as an avoidable cause of cancer in Europe
Bergström, A., Pisani, P., Tenet, V., Wolk, A., & Adami, H. (2001) · International Journal of Cancer · doi:10.1002/1097-0215(200002)9999:9999 · Cited by 772 · see citing works
Probability and the Weighing of Evidence.
M., P. A., & Good, I. J. (1950) · Journal of the Royal Statistical Society Series A (General) · doi:10.2307/2981046 · Cited by 753 · see citing works
Bayesian approaches to randomized trials
Spiegelhalter, D. J., Freedman, L. S., & Parmar, M. K. B. (1994) · Journal of the Royal Statistical Society. Series A (Statistics in Society) · doi:10.2307/2983527 · Cited by 720 · see citing works
CASE-CONTROL STUDY OF CHILDHOOD CANCER AND EXPOSURE TO 60-HZ MAGNETIC FIELDS
Savitz, D. A., Wachtel, H., BARNES, F. A., John, E. M., & TVRDIK, J. G. (1988) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a114943 · Cited by 707 · see citing works
Basic methods for sensitivity analysis of biases.
Greenland, S. (1996) · International Journal of Epidemiology · doi:10.1093/ije/25.6.1107 · Cited by 605 · see citing works
Heitjan, D. F., & Rubin, D. B. (1991) · The Annals of Statistics · doi:10.1214/aos/1176348396 · Cited by 591 · see citing works
Bayesian approaches to random-effects meta-analysis: a comparative study
Smith, T. C., Spiegelhalter, D. J., & Thomas, A. (1995) · Statistics in Medicine · doi:10.1002/sim.4780142408 · Cited by 568 · see citing works
A Pooled Analysis of Magnetic Fields, Wire Codes, and Childhood Leukemia
Greenland, S., Sheppard, A. R., Kaune, W. T., Poole, C., & Kelsh, M. A. (2000) · Epidemiology · doi:10.1097/00001648-200011000-00003 · Cited by 526 · see citing works
Magnetic Fields and Cancer in Children Residing Near Swedish High-voltage Power Lines
Feychting, M., & Alhbom, M. (1993) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a116881 · Cited by 511 · see citing works
Exposure to Residential Electric and Magnetic Fields and Risk of Childhood Leukemia
London, S. J., Thomas, D. C., Bowman, J. D., Sobel, E. L., Cheng, T.-C., & Peters, J. M. (1991) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a116176 · Cited by 451 · see citing works
Lawlor, D. A., Smith, G. D., Bruckdorfer, K. R., Kundu, D., & Ebrahim, S. (2004) · The Lancet · doi:10.1016/s0140-6736(04)16260-0 · Cited by 438 · see citing works
Residential Exposure to Magnetic Fields and Acute Lymphoblastic Leukemia in Children
Linet, M. S., Hatch, E. E., Kleinerman, R. A., Robison, L. L., Kaune, W. T., Friedman, D. R., Severson, R. K., Haines, C. M., Hartsock, C. T., Niwa, S., et al. (1997) · New England Journal of Medicine · doi:10.1056/nejm199707033370101 · Cited by 416 · see citing works
The economics ofAccounting for Growth
Pierce‐Brown, R., & Steele, T. (1999) · Accounting and Business Research · doi:10.1080/00014788.1999.9729576 · Cited by 401 · see citing works
Inference for Non-random Samples
Copas, J. B., & Li, H. G. (1997) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/1467-9868.00055 · Cited by 398 · see citing works
Formalizing Subjective Notions About the Effect of Nonrespondents in Sample Surveys
Rubin, D. B. (1977) · Journal of the American Statistical Association · doi:10.1080/01621459.1977.10480610 · Cited by 381 · see citing works
Robins, J. M., Rotnitzky, A. G., & Scharfstein, D. O. (2000) · The IMA volumes in mathematics and its applications · doi:10.1007/978-1-4612-1284-3_1 · Cited by 371 · see citing works
Problems due to Small Samples and Sparse Data in Conditional Logistic Regression Analysis
Greenland, S., Schwartzbaum, J., & Finkle, W. D. (2000) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a010240 · Cited by 367 · see citing works
Multilevel Analysis of Educational Data
(1989) · Elsevier eBooks · doi:10.1016/c2009-0-21681-3 · Cited by 365 · see citing works
50‐Hz electromagnetic environment and the incidence of childhood tumors in Stockholm county
Tomenius, L. (1986) · Bioelectromagnetics · doi:10.1002/bem.2250070209 · Cited by 312 · see citing works
Identification of Causal Effects Using Instrumental Variables: Comment
Robins, J. M., & Greenland, S. (1996) · Journal of the American Statistical Association · doi:10.2307/2291630 · Cited by 296 · see citing works
A method to automate probabilistic sensitivity analyses of misclassified binary variables.
Fox, M., Lash, T., & Greenland, S. (2005) · International Journal of Epidemiology · doi:10.1093/ije/dyi184 · Cited by 287 · see citing works
Differential Misclassification Arising from Nondifferential Errors in Exposure Measurement
Flegal, K. M., Keyl, P. M., & Nieto, F. J. (1991) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a116026 · Cited by 283 · see citing works
Inference for imputation estimators
Robins, J. M. (2000) · Biometrika · doi:10.1093/biomet/87.1.113 · Cited by 278 · see citing works
Statistical Models in Epidemiology
K., M., Clayton, D. G., & Hills, M. (1995) · Population · doi:10.2307/1534207 · Cited by 272 · see citing works
Odds Ratio Estimators When the Data are Sparse
Breslow, N. E. (1981) · Biometrika · doi:10.1093/biomet/68.1.73 · Cited by 260 · see citing works
Semi-Automated Sensitivity Analysis to Assess Systematic Errors in Observational Data
Lash, T. L., & Fink, A. K. (2003) · Epidemiology · doi:10.1097/01.ede.0000071419.41011.cf · Cited by 250 · see citing works
Measurement Error and Misclassification in Statistics and Epidemiology
Gustafson, P. (2003) · Chapman & Hall/CRC eBooks · doi:10.1201/9780203502761 · Cited by 249 · see citing works
Residence near high voltage facilities and risk of cancer in children.
Olsen, J. H., Nielsen, A., & Schulgen, G. (1993) · BMJ · doi:10.1136/bmj.307.6909.891 · Cited by 248 · see citing works
CONFOUNDING AND MISCLASSIFICATION
Greenland, S., & Robins, J. M. (1985) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a114131 · Cited by 232 · see citing works
Risk of cancer in Finnish children living close to power lines.
Verkasalo, P. K., Pukkala, ., Hongisto, M., Valjus, J., Järvinen, P., Heikkila, K. V., & Koskenvuo, M. (1993) · BMJ · doi:10.1136/bmj.307.6909.895 · Cited by 223 · see citing works
Diagnostics for Multivariate Imputations
Abayomi, K., Gelman, A., & Levy, M. A. (2008) · Journal of the Royal Statistical Society Series C (Applied Statistics) · doi:10.1111/j.1467-9876.2007.00613.x · Cited by 220 · see citing works
Power-Frequency Electric and Magnetic Fields and Risk of Childhood Leukemia in Canada
McBride, M. L., Gallagher, R. P., Theriault, G. P., Armstrong, B., Tamaro, S., Spinelli, J. J., Deadman, J. E., Fincham, S. M., Robson, D., & Choi, W. N. (1999) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a009899 · Cited by 218 · see citing works
Steenland, K. (2004) · American Journal of Epidemiology · doi:10.1093/aje/kwh211 · Cited by 208 · see citing works
Interval estimation by simulation as an alternative to and extension of confidence intervals.
Greenland, S. (2004) · International Journal of Epidemiology · doi:10.1093/ije/dyh276 · Cited by 202 · see citing works
Gustafson, P. (2005) · Statistical Science · doi:10.1214/088342305000000098 · Cited by 185 · see citing works
Exposure to power-frequency magnetic fields and the risk of childhood cancer
(1999) · The Lancet · doi:10.1016/s0140-6736(99)10074-6 · Cited by 184 · see citing works
Sensitivity Analysis, Monte Carlo Risk Analysis, and Bayesian Uncertainty Assessment
Greenland, S. (2001) · Risk Analysis · doi:10.1111/0272-4332.214136 · Cited by 174 · see citing works
What Works?: Selectivity Models and Meta-Analysis
Copas, J. B. (1999) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/1467-985x.00123 · Cited by 168 · see citing works
Quantifying and Reporting Uncertainty from Systematic Errors
Phillips, C. V. (2003) · Epidemiology · doi:10.1097/01.ede.0000072106.65262.ae · Cited by 168 · see citing works
Validation Studies using an Alloyed Gold Standard
Wacholder, S., Armstrong, B., & Hartge, P. (1993) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a116627 · Cited by 161 · see citing works
Electromagnetic Fields and Cancer in Children Residing Near Norwegian High-Voltage Power Lines
Tynes, T., & Haldorsen, T. (1997) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a009094 · Cited by 158 · see citing works
Tests for Trend and Dose Response: Misinterpretations and Alternatives
Madure, M., & Greenland, S. (1992) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a116206 · Cited by 154 · see citing works
Inference and Hierarchical Modeling in the Social Sciences
Draper, D. (1995) · Journal of Educational and Behavioral Statistics · doi:10.3102/10769986020002115 · Cited by 152 · see citing works
Exposure-measurement error is frequently ignored when interpreting epidemiologic study results
Jurek, A. M., Maldonado, G., Greenland, S., & Church, T. R. (2006) · European Journal of Epidemiology · doi:10.1007/s10654-006-9083-0 · Cited by 147 · see citing works
Meta-analysis by the confidence profile method
Eddy, D. M. (1992) · Cited by 144 · see citing works
Greenland, S. (2003) · Journal of the American Statistical Association · doi:10.1198/01621450338861905 · Cited by 141 · see citing works
Self-citationCausation of Bias: The Episcope
Maclure, M., & Schneeweiß, S. (2001) · Epidemiology · doi:10.1097/00001648-200101000-00019 · Cited by 128 · see citing works
Lawlor, D. A. (2004) · International Journal of Epidemiology · doi:10.1093/ije/dyh124 · Cited by 109 · see citing works
Binomial Regression with Misclassification
Paulino, C. D., Soares, P., & Neuhaus, J. M. (2003) · Biometrics · doi:10.1111/1541-0420.00077 · Cited by 107 · see citing works
Sensitivity Analysis for Incomplete Contingency Tables: The Slovenian Plebiscite Case
Molenberghs, G., Kenward, M. G., & Goetghebeur, E. J. T. (2001) · Journal of the Royal Statistical Society Series C (Applied Statistics) · doi:10.1111/1467-9876.00217 · Cited by 98 · see citing works
Dendukuri, N., Rahme, E., Bélisle, P., & Joseph, L. (2004) · Biometrics · doi:10.1111/j.0006-341x.2004.00183.x · Cited by 98 · see citing works
Local Sensitivity Approximations for Selectivity Bias
Copas, J. B., & Eguchi, S. (2001) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/1467-9868.00318 · Cited by 88 · see citing works
Electromagnetic Field Exposures and Childhood Cancers in New Zealand
Dockerty, J. D., Elwood, M., Skegg, D. C. G., & Herbison, P. (1998) · Cancer Causes & Control · doi:10.1023/a:1008825220759 · Cited by 87 · see citing works
Case-control studies: Assessing the effect of a confounding factor
Yanagawa, T. (1984) · Biometrika · doi:10.1093/biomet/71.1.191 · Cited by 87 · see citing works
UK Childhood Cancer Study Investigators
Beral, V., Alexander, F. E., & Appleby, P. N. (2001) · Cited by 86 · see citing works
Eliciting and using expert opinions about dropout bias in randomized controlled trials
White, I. R., Carpenter, J. R., Evans, S. J. W., & Schroter, S. (2007) · Clinical Trials · doi:10.1177/1740774507077849 · Cited by 85 · see citing works
A Potential Pitfall in Control of Covariates in Epidemiologic Studies
Brenner, H. (1998) · Epidemiology · doi:10.1097/00001648-199801000-00014 · Cited by 84 · see citing works
Measurement Error and Misclassification in Statistics and Epidemiology
Spiegelman, D. L. (2006) · Journal of the American Statistical Association · doi:10.1198/jasa.2006.s70 · Cited by 80 · see citing works
A Bayesian approach to sensitivity analysis
Felli, J. C., & Hazen, G. B. (1999) · Health Economics · doi:10.1002/(sici)1099-1050(199905)8:3 · Cited by 77 · see citing works
Consensus and Controversy in Pharmaceutical Statistics
Senn, S. J. (2000) · Journal of the Royal Statistical Society Series D (The Statistician) · doi:10.1111/1467-9884.00227 · Cited by 77 · see citing works
Commentary: Hormone replacement therapy and coronary heart disease: four lessons
Petitti, D. B. (2004) · International Journal of Epidemiology · doi:10.1093/ije/dyh192 · Cited by 72 · see citing works
Hatch, E. E., Kleinerman, R. A., Linet, M. S., Tarone, R. E., Kaune, W. T., Auvinen, A. P., Baris, D., Robison, L. L., & Wacholder, S. (2000) · Epidemiology · doi:10.1097/00001648-200003000-00019 · Cited by 68 · see citing works
The economics of ‘more research is needed’
Phillips, C. V. (2001) · International Journal of Epidemiology · doi:10.1093/ije/30.4.771 · Cited by 66 · see citing works
False Models and Post-Data Model Construction
Leamer, E. E. (1974) · Journal of the American Statistical Association · doi:10.1080/01621459.1974.10480138 · Cited by 64 · see citing works
A Bound for Publication Bias Based on the Fraction of Unpublished Studies
Copas, J. B., & Jackson, D. (2004) · Biometrics · doi:10.1111/j.0006-341x.2004.00161.x · Cited by 64 · see citing works
Rahme, E., Joseph, L., & Gyorkos, T. W. (2000) · Journal of the Royal Statistical Society Series C (Applied Statistics) · doi:10.1111/1467-9876.00182 · Cited by 61 · see citing works
Childhood leukemia: electric and magnetic fields as possible risk factors.
Brain, J. D., Kavet, R. I., McCormick, D. L., Poole, C., Silverman, L. B., Smith, T. J., Valberg, P. A., Etten, R. A. V., & Weaver, J. C. (2003) · Environmental Health Perspectives · doi:10.1289/ehp.6020 · Cited by 59 · see citing works
Methods for Assessing the Credibility of Clinical Trial Outcomes
Matthews, R. (2001) · Drug Information Journal · doi:10.1177/009286150103500442 · Cited by 57 · see citing works
Michaelis, J., Schüz, J., Meinert, R., Zemann, E., Grigat, J.-P., Kaatsch, P., Kaletsch, U., Miesner, A., Brinkmann, K., Kalkner, W., et al. (1998) · Epidemiology · doi:10.1097/00001648-199801000-00018 · Cited by 57 · see citing works
ELF Electromagnetic fields and the risk of cancer
Meade, T. W. (2001) · LSHTM Research Online (London School of Hygiene and Tropical Medicine) · Cited by 55 · see citing works
Functional reassessment of P16 variants using a transfection-based assay
Walker, G. J., Gabrielli, B. G., Castellano, M., & Hayward, N. K. (1999) · International Journal of Cancer · doi:10.1002/(sici)1097-0215(19990719)82:2 · Cited by 55 · see citing works
Maldonado, G., & Poole, C. (1999) · Annals of Epidemiology · doi:10.1016/s1047-2797(98)00050-7 · Cited by 55 · see citing works
Coghill, R., Steward, J. K., & Philips, A. (1996) · European Journal of Cancer Prevention · doi:10.1097/00008469-199606000-00002 · Cited by 54 · see citing works
Generalized Conjugate Priors for Bayesian Analysis of Risk and Survival Regressions
Greenland, S. (2003) · Biometrics · doi:10.1111/1541-0420.00011 · Cited by 52 · see citing works
Residential EMF exposure and childhood leukemia: Meta-analysis and population attributable risk
Wartenberg, D. E. (2001) · Bioelectromagnetics · doi:10.1002/1521-186x(2001)22:5+ · Cited by 51 · see citing works
Putting Background Information About Relative Risks into Conjugate Prior Distributions
Greenland, S. (2001) · Biometrics · doi:10.1111/j.0006-341x.2001.00663.x · Cited by 50 · see citing works
Lash, T., & Silliman, R. (2000) · Epidemiology · doi:10.1097/00001648-200009000-00010 · Cited by 47 · see citing works
Rice, K. M. (2004) · Journal of the American Statistical Association · doi:10.1198/016214504000000511 · Cited by 41 · see citing works
(2005) · Choice Reviews Online · doi:10.5860/choice.43-1298 · Cited by 40 · see citing works
Considering uncertainty in comparing the burden of illness due to foodborne microbial pathogens
Powell, M. R., Ebel, E. D., & Schlosser, W. D. (2001) · International Journal of Food Microbiology · doi:10.1016/s0168-1605(01)00495-0 · Cited by 32 · see citing works
Kavet, R. I., & Zaffanella, L. E. (2002) · Bioelectromagnetics · doi:10.1002/bem.10038 · Cited by 31 · see citing works
The sensitivity of sensitivity analysis
Plümper, T., & Traunmüller, R. (2018) · Political Science Research and Methods · doi:10.1017/psrm.2018.30 · Cited by 29 · see citing works
Domiciliary thrombolysis by general practitioners.
Pocock, S., & Spiegelhalter, D. J. (1992) · BMJ · doi:10.1136/bmj.305.6860.1015 · Cited by 28 · see citing works
Electromagnetic Fields and Cancer
Jauchem, J. R. (1990) · Science · doi:10.1126/science.1700478 · Cited by 25 · see citing works
Full‐likelihood approaches to misclassification of a binary exposure in matched case‐control studies
Rice, K. M. (2003) · Statistics in Medicine · doi:10.1002/sim.1546 · Cited by 23 · see citing works
Inference and Hierarchical Modeling in the Social Sciences
Draper, D. (1995) · Journal of Educational and Behavioral Statistics · doi:10.2307/1165353 · Cited by 23 · see citing works
FISHER SCORING ALGORITHM FOR VARIANCE COMPONENT ANALYSIS OF DATA WITH MULTILEVEL STRUCTURE
Longford, N. T. (1989) · Elsevier eBooks · doi:10.1016/b978-0-12-108840-8.50019-6 · Cited by 22 · see citing works
Inference and Disputed Authorship: The Federalist
Webb, L. M., Webb, S. S., Mosteller, F. C., & Wallace, D. L. (1966) · The William and Mary Quarterly · doi:10.2307/1922539 · Cited by 22 · see citing works
Information on Sexual Behaviour when some Data are Missing
RAAB, G. M., & Donnelly, C. A. (1999) · Journal of the Royal Statistical Society Series C (Applied Statistics) · doi:10.1111/1467-9876.00144 · Cited by 21 · see citing works
Bracken, M. B., Belanger, K. D., HELLENBRAND, K. G., Addesso, K., Patel, S., Triche, E. W., & Leaderer, B. P. (1998) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a009672 · Cited by 16 · see citing works
Rubin, D. B. (1983) · Elsevier eBooks · doi:10.1016/b978-0-12-121160-8.50017-x · Cited by 15 · see citing works
Synthetic estimators with moderating influence: the carry‐over in cross‐over trials revisited
Longford, N. T. (2001) · Statistics in Medicine · doi:10.1002/sim.926 · Cited by 12 · see citing works
How a Court Accepted a Possible Explanation: A Comment on Gastwirth, Krieger, and Rosenbaum
Poole, C., & Greenland, S. (1997) · The American Statistician · doi:10.1080/00031305.1997.10473940 · Cited by 6 · see citing works
Crouch, E. A. C., Lester, R. R., Lash, T. L., Armstrong, S. R., & Green, L. C. (1997) · Human and Ecological Risk Assessment An International Journal · doi:10.1080/10807039709383730 · Cited by 6 · see citing works
Qiu, P., Moeschberger, M. L., Cooke, G. E., & Goldschmidt‐Clermont, P. J. (2000) · Statistics in Medicine · doi:10.1002/(sici)1097-0258(20000415)19:7 · Cited by 5 · see citing works
DISCUSSION OF AITKIN'S AND LONGFORD'S PAPERS
Holland, P. W. (1989) · Elsevier eBooks · doi:10.1016/b978-0-12-108840-8.50020-2 · Cited by 1 · see citing works
Assessing sensitivity to unmeasured confounding in observational studies : a bayesian approach
McCandless, L. C. (2009) · cIRcle (University of British Columbia) · doi:10.14288/1.0091699 · Cited by 1 · see citing works
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Sensitivity analysis in observational research: Introducing the E-value
VanderWeele, T. J., & Ding, P. (2017) · Annals of Internal Medicine · doi:10.7326/m16-2607 · Cited by 6,350 · see citing works
A Re-Evaluation of Random-Effects Meta-Analysis
Higgins, J. P. T., Thompson, S. G., & Spiegelhalter, D. J. (2009) · Journal of the Royal Statistical Society Series A: Statistics in Society · doi:10.1111/j.1467-985x.2008.00552.x · Cited by 2,569 · see citing works
“Alternative approaches to dealing with specific sources of bias are available (Eddy et al., 1992; Greenland, 2005).”
BackgroundOrsini, N., Li, R., Wolk, A., Khudyakov, P., & Spiegelman, D. L. (2011) · American Journal of Epidemiology · doi:10.1093/aje/kwr265 · Cited by 1,276 · see citing works
Generalized Least Squares for Trend Estimation of Summarized Dose–response Data
Orsini, N., Bellocco, R., & Greenland, S. (2006) · The Stata Journal Promoting communications on statistics and Stata · doi:10.1177/1536867x0600600103 · Cited by 1,245 · see citing works
Kalantar‐Zadeh, K., Kuwae, N., Regidor, D. L., Kovesdy, C. P., Kilpatrick, R. D., Shinaberger, C. S., McAllister, C. J., Budoff, M. J., Salusky, I. B., & Kopple, J. D. (2006) · Kidney International · doi:10.1038/sj.ki.5001514 · Cited by 900 · see citing works
Schneeweiß, S. (2006) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.1200 · Cited by 731 · see citing works
Hamling, J., Lee, P. N., Weitkunat, R., & Ambühl, M. (2007) · Statistics in Medicine · doi:10.1002/sim.3013 · Cited by 649 · see citing works
Good practices for quantitative bias analysis
Lash, T. L., Fox, M. P., MacLehose, R. F., Maldonado, G., McCandless, L. C., & Greenland, S. (2014) · International Journal of Epidemiology · doi:10.1093/ije/dyu149 · Cited by 651 · see citing works
Recent developments in meta‐analysis
Sutton, A. J., & Higgins, J. P. T. (2007) · Statistics in Medicine · doi:10.1002/sim.2934 · Cited by 583 · see citing works
VanderWeele, T. J., & Arah, O. A. (2010) · Epidemiology · doi:10.1097/ede.0b013e3181f74493 · Cited by 455 · see citing works
Proper interpretation of non-differential misclassification effects: expectations vs observations
Jurek, A. M., Greenland, S., Maldonado, G., & Church, T. R. (2005) · International Journal of Epidemiology · doi:10.1093/ije/dyi060 · Cited by 413 · see citing works
GetReal in network meta-analysis: a review of the methodology
Efthimiou, O., Debray, T. P. A., van Valkenhoef, G., Trelle, S., Panayidou, K., Moons, K. G. M., Reitsma, J. B., Shang, A., Salanti, G., & on behalf of GetReal Methods Review Group (2016) · Research Synthesis Methods · doi:10.1002/jrsm.1195 · Cited by 401 · see citing works
Bayesian perspectives for epidemiological research: I. Foundations and basic methods
Greenland, S. (2006) · International Journal of Epidemiology · doi:10.1093/ije/dyi312 · Cited by 383 · see citing works
The Bradford Hill considerations on causality: a counterfactual perspective
Höfler, M. (2005) · Emerging Themes in Epidemiology · doi:10.1186/1742-7622-2-11 · Cited by 341 · see citing works
Bias Modelling in Evidence Synthesis
Turner, R., Spiegelhalter, D. J., Smith, G. C. S., & Thompson, S. G. (2008) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/j.1467-985x.2008.00547.x · Cited by 322 · see citing works
A Review of Generalizability and Transportability
Degtiar, I., & Rose, S. (2022) · Annual Review of Statistics and Its Application · doi:10.1146/annurev-statistics-042522-103837 · Cited by 299 · see citing works
A method to automate probabilistic sensitivity analyses of misclassified binary variables.
Fox, M., Lash, T., & Greenland, S. (2005) · International Journal of Epidemiology · doi:10.1093/ije/dyi184 · Cited by 287 · see citing works
Prospective study design and data analysis in UK Biobank
Allen, N. E., Lacey, B., Lawlor, D. A., Pell, J. P., Gallacher, J., Smeeth, L. L., Elliott, P., Matthews, P. M., Lyons, R. A., Whetton, A. D., et al. (2024) · Science Translational Medicine · doi:10.1126/scitranslmed.adf4428 · Cited by 289 · see citing works
Invited Commentary: Variable Selection versus Shrinkage in the Control of Multiple Confounders
Greenland, S. (2007) · American Journal of Epidemiology · doi:10.1093/aje/kwm355 · Cited by 281 · see citing works
Statistical Foundations for Model-Based Adjustments
Greenland, S., & Pearce, N. E. (2015) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-031914-122559 · Cited by 274 · see citing works
Hashibe, M., Morgenstern, H., Cui, Y., Tashkin, D. P., Zhang, Z., Cozen, W., Mack, T. M., & Greenland, S. (2006) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-06-0330 · Cited by 256 · see citing works
Ioannidis, J. P. A. (2011) · JAMA · doi:10.1001/jama.2011.713 · Cited by 253 · see citing works
Beyond Subjective and Objective in Statistics
Gelman, A., & Hennig, C. M. (2017) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/rssa.12276 · Cited by 257 · see citing works
Causal inference based on counterfactuals
Höfler, M. (2005) · BMC Medical Research Methodology · doi:10.1186/1471-2288-5-28 · Cited by 246 · see citing works
A road map for efficient and reliable human genome epidemiology.
The Human Genome Epidemiology Network and the Network of Investigator Networks, Ioannidis, J. P. A., Gwinn, M., Little, J., Higgins, J. P. T., Bernstein, J. L., Boffetta, P., Bondy, M., Bray, M. S., Brenchley, P. E., et al. (2006) · Nature Genetics · doi:10.1038/ng0106-3 · Cited by 244 · see citing works
Ambient Air Pollution and Adverse Birth Outcomes: Methodologic Issues in an Emerging Field
Ritz, B. R., & Wilhelm, M. H. (2008) · Basic & Clinical Pharmacology & Toxicology · doi:10.1111/j.1742-7843.2007.00161.x · Cited by 244 · see citing works
Causal Directed Acyclic Graphs and the Direction of Unmeasured Confounding Bias
VanderWeele, T. J., Hernán, M. Á., & Robins, J. M. (2008) · Epidemiology · doi:10.1097/ede.0b013e3181810e29 · Cited by 234 · see citing works
Feychting, M., Ahlbom, A., & Kheifets, L. (2004) · Annual Review of Public Health · doi:10.1146/annurev.publhealth.26.021304.144445 · Cited by 234 · see citing works
Causal Models and Learning from Data
Petersen, M. L., & van der Laan, M. J. (2014) · Epidemiology · doi:10.1097/ede.0000000000000078 · Cited by 232 · see citing works
Nitsch, D., Molokhia, M., Smeeth, L. L., Stavola, B. L. D., Whittaker, J. C., & Leon, D. A. (2006) · American Journal of Epidemiology · doi:10.1093/aje/kwj062 · Cited by 228 · see citing works
Steenland, K. (2004) · American Journal of Epidemiology · doi:10.1093/aje/kwh211 · Cited by 208 · see citing works
Interactions in epidemiology: relevance, identification, and estimation
Greenland, S. (2009) · Epidemiology · doi:10.1097/ede.0b013e318193e7b5 · Cited by 204 · see citing works
Bayesian perspectives for epidemiological research. II. Regression analysis
Greenland, S. (2007) · International Journal of Epidemiology · doi:10.1093/ije/dyl289 · Cited by 200 · see citing works
Personality, Socioeconomic Status, and All-Cause Mortality in the United States
Chapman, B. P., Fiscella, K., Kawachi, I., & Duberstein, P. R. (2010) · American Journal of Epidemiology · doi:10.1093/aje/kwp323 · Cited by 198 · see citing works
Gustafson, P. (2005) · Statistical Science · doi:10.1214/088342305000000098 · Cited by 185 · see citing works
Bayesian sensitivity analysis for unmeasured confounding in observational studies
McCandless, L. C., Gustafson, P., & Levy, A. R. (2006) · Statistics in Medicine · doi:10.1002/sim.2711 · Cited by 182 · see citing works
Adjusting for selection bias in retrospective, case-control studies
Geneletti, S., Richardson, S., & Best, N. (2008) · Biostatistics · doi:10.1093/biostatistics/kxn010 · Cited by 174 · see citing works
Measurement bias and effect restoration in causal inference
Kuroki, M., & Pearl, J. (2014) · Biometrika · doi:10.1093/biomet/ast066 · Cited by 164 · see citing works
Bounding Bias Due to Selection
Smith, L. H., & VanderWeele, T. J. (2019) · Epidemiology · doi:10.1097/ede.0000000000001032 · Cited by 168 · see citing works
Combining randomized and non-randomized evidence in network meta-analysis
Efthimiou, O., Mavridis, D., Debray, T. P. A., Samara, M., Belger, M., Siontis, G. C. M., Leucht, S., Salanti, G., & 4, O. B. O. G. W. P. (2017) · Statistics in Medicine · doi:10.1002/sim.7223 · Cited by 183 · see citing works
Multiparameter Evidence Synthesis in Epidemiology and Medical Decision-Making: Current Approaches
Ades, A. E., & Sutton, A. J. (2005) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/j.1467-985x.2005.00377.x · Cited by 159 · see citing works
Use of photosensitising diuretics and risk of skin cancer: a population-based case–control study
Jensen, A. Ø., Thomsen, H. F., Engebjerg, M. C., Olesen, A. B., Sørensen, H. T., & Karagas, M. R. (2008) · British Journal of Cancer · doi:10.1038/sj.bjc.6604686 · Cited by 155 · see citing works
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Greenland, S., & Robins, J. M. (2009) · Epidemiologic Perspectives & Innovations · doi:10.1186/1742-5573-6-4 · Cited by 155 · see citing works
Jurek, A. M., Greenland, S., & Maldonado, G. (2008) · International Journal of Epidemiology · doi:10.1093/ije/dym291 · Cited by 151 · see citing works
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Welton, N. J., Ades, A. E., Carlin, J. B., Altman, D. G., & Sterne, J. A. C. (2008) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/j.1467-985x.2008.00548.x · Cited by 150 · see citing works
Hartman, E., Grieve, R., Ramsahai, R. R., & Sekhon, J. S. (2015) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/rssa.12094 · Cited by 145 · see citing works
Exposure-measurement error is frequently ignored when interpreting epidemiologic study results
Jurek, A. M., Maldonado, G., Greenland, S., & Church, T. R. (2006) · European Journal of Epidemiology · doi:10.1007/s10654-006-9083-0 · Cited by 147 · see citing works
McGowan, C. C., Cahn, P. E., Gotuzzo, E., Padgett, D., Pape, J. W., Wolff, M. J., Schechter, M., & Masys, D. R. (2007) · International Journal of Epidemiology · doi:10.1093/ije/dym073 · Cited by 141 · see citing works
Sensitivity analyses to estimate the potential impact of unmeasured confounding in causal research
Groenwold, R. H. H., Nelson, D. B., Nichol, K. L., Hoes, A. W., & Hak, E. (2009) · International Journal of Epidemiology · doi:10.1093/ije/dyp332 · Cited by 127 · see citing works
Towards more Accessible Conceptions of Statistical Inference
Wild, C. J., Pfannkuch, M., Regan, M., & Horton, N. J. (2011) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/j.1467-985x.2010.00678.x · Cited by 126 · see citing works
Verde, P. E., & Ohmann, C. (2015) · Research Synthesis Methods · doi:10.1002/jrsm.1122 · Cited by 123 · see citing works
Triangulating Evidence through the Inclusion of Genetically Informed Designs
Munafò, M. R., Higgins, J. P. T., & Smith, G. D. (2021) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a040659 · Cited by 125 · see citing works
A Tool for Deterministic and Probabilistic Sensitivity Analysis of Epidemiologic Studies
Orsini, N., Bellocco, R., Bottai, M., Wolk, A., & Greenland, S. (2008) · The Stata Journal Promoting communications on statistics and Stata · doi:10.1177/1536867x0800800103 · Cited by 122 · see citing works
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Lash, T. L., Mor, V., Wieland, D., Ferrucci, L., Satariano, W. A., & Silliman, R. A. (2007) · The Journals of Gerontology Series A · doi:10.1093/gerona/62.3.281 · Cited by 118 · see citing works
Sarri, G., Patorno, E., Yuan, H., Guo, J., Bennett, D., Wen, X., Zullo, A. R., Largent, J. A., Panaccio, M. P., Gokhale, M., et al. (2020) · BMJ Evidence-Based Medicine · doi:10.1136/bmjebm-2020-111493 · Cited by 120 · see citing works
The effect of misclassification on the estimation of association: a review
Höfler, M. (2005) · International Journal of Methods in Psychiatric Research · doi:10.1002/mpr.20 · Cited by 115 · see citing works
On Instrumental Variables Estimation of Causal Odds Ratios
Vansteelandt, S., Bowden, J., Babanezhad, M., & Goetghebeur, E. J. T. (2011) · Statistical Science · doi:10.1214/11-sts360 · Cited by 116 · see citing works
Allowing for uncertainty due to missing data in meta‐analysis—Part 1: Two‐stage methods
White, I. R., Higgins, J. P. T., & Wood, A. (2007) · Statistics in Medicine · doi:10.1002/sim.3008 · Cited by 114 · see citing works
Combining Survey Data with Other Data Sources
Lohr, S. L., & Raghunathan, T. E. (2017) · Statistical Science · doi:10.1214/16-sts584 · Cited by 115 · see citing works
Uncertainty in Clinical Medicine
Djulbegović, B., Hozo, I., & Greenland, S. (2011) · Elsevier eBooks · doi:10.1016/b978-0-444-51787-6.50011-8 · Cited by 110 · see citing works
Bias Formulas for External Adjustment and Sensitivity Analysis of Unmeasured Confounders
Arah, O. A., Chiba, Y., & Greenland, S. (2008) · Annals of Epidemiology · doi:10.1016/j.annepidem.2008.04.003 · Cited by 107 · see citing works
Bayesian perspectives for epidemiologic research: III. Bias analysis via missing-data methods
Greenland, S. (2009) · International Journal of Epidemiology · doi:10.1093/ije/dyp278 · Cited by 107 · see citing works
A proposed method of bias adjustment for meta-analyses of published observational studies
Thompson, S., Ekelund, U., Jebb, S., Lindroos, A. K., Mander, A., Sharp, S., Turner, R., & Wilks, D. (2011) · International Journal of Epidemiology · doi:10.1093/ije/dyq248 · Cited by 101 · see citing works
Quality of reporting of confounding remained suboptimal after the STROBE guideline
Pouwels, K. B., Widyakusuma, N. N., Groenwold, R. H. H., & Hak, E. (2015) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2015.08.009 · Cited by 103 · see citing works
Public Health Impact of Extremely Low-Frequency Electromagnetic Fields
Kheifets, L., Afifi, A. A., & Shimkhada, R. (2006) · Environmental Health Perspectives · doi:10.1289/ehp.8977 · Cited by 102 · see citing works
Jensen, A. Ø., Thomsen, H. F., Engebjerg, M. C., Olesen, A. B., Friis, S., Karagas, M. R., & Sørensen, H. T. (2008) · British Journal of Cancer · doi:10.1038/sj.bjc.6604796 · Cited by 101 · see citing works
Statistical Issues Arising in the Women's Health Initiative
Prentice, R. L., Pettinger, M. B., & Anderson, G. L. (2005) · Biometrics · doi:10.1111/j.0006-341x.2005.454_1.x · Cited by 99 · see citing works
Childhood leukemia and EMF: Review of the epidemiologic evidence
Kheifets, L., & Shimkhada, R. (2005) · Bioelectromagnetics · doi:10.1002/bem.20139 · Cited by 95 · see citing works
Common misconceptions about validation studies
Fox, M. P., Lash, T. L., & Bodnar, L. M. (2020) · International Journal of Epidemiology · doi:10.1093/ije/dyaa090 · Cited by 94 · see citing works
Kitsios, G. D., Dahabreh, I. J., Callahan, S. P., Paulus, J. K., Campagna, A. C., & Dargin, J. (2015) · Critical Care Medicine · doi:10.1097/ccm.0000000000001135 · Cited by 92 · see citing works
Modeling conditional dependence between diagnostic tests: A multiple latent variable model
Dendukuri, N., Hadgu, A., & Wang, L. (2008) · Statistics in Medicine · doi:10.1002/sim.3470 · Cited by 91 · see citing works
Heuristic Thinking and Inference From Observational Epidemiology
Lash, T. (2007) · Epidemiology · doi:10.1097/01.ede.0000249522.75868.16 · Cited by 95 · see citing works
Groene, O., Klazinga, N., Wagner, C., Arah, O. A., Thompson, A. G. H., Bruneau, C., & Suñol, R. (2010) · BMC Health Services Research · doi:10.1186/1472-6963-10-281 · Cited by 87 · see citing works
Bayesian regression in SAS software
Sullivan, S. G., & Greenland, S. (2012) · International Journal of Epidemiology · doi:10.1093/ije/dys213 · Cited by 87 · see citing works
Gold Standards in Pharmacovigilance
Hauben, M., & Aronson, J. K. (2007) · Drug Safety · doi:10.2165/00002018-200730080-00001 · Cited by 86 · see citing works
Eliciting and using expert opinions about dropout bias in randomized controlled trials
White, I. R., Carpenter, J. R., Evans, S. J. W., & Schroter, S. (2007) · Clinical Trials · doi:10.1177/1740774507077849 · Cited by 85 · see citing works
Dias, S., Welton, N. J., Marinho, V. C., Salanti, G., Higgins, J. P. T., & Ades, A. E. (2010) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/j.1467-985x.2010.00639.x · Cited by 85 · see citing works
Gelman, A. (2011) · American Journal of Sociology · doi:10.1086/662659 · Cited by 85 · see citing works
Greenland, S. (2020) · Paediatric and Perinatal Epidemiology · doi:10.1111/ppe.12711 · Cited by 83 · see citing works
Sensitivity Analysis of Misclassification: A Graphical and a Bayesian Approach
Chu, H., Wang, Z., Cole, S. R., & Greenland, S. (2006) · Annals of Epidemiology · doi:10.1016/j.annepidem.2006.04.001 · Cited by 83 · see citing works
Cole, S. R., Hudgens, M. G., Brookhart, M. A., & Westreich, D. J. (2015) · American Journal of Epidemiology · doi:10.1093/aje/kwv001 · Cited by 82 · see citing works
Schwahn, C., Frenzel, S., Holtfreter, B., der Auwera, S. V., Pink, C., Bülow, R., Friedrich, N., Völzke, H., Biffar, R., Kocher, T., et al. (2021) · Alzheimer s & Dementia · doi:10.1002/alz.12378 · Cited by 91 · see citing works
Stürmer, T., Glynn, R. J., Rothman, K. J., Avorn, J., & Schneeweiß, S. (2007) · Medical Care · doi:10.1097/mlr.0b013e318070c045 · Cited by 81 · see citing works
Epidemiologic measures and policy formulation: lessons from potential outcomes
Greenland, S. (2005) · Emerging Themes in Epidemiology · doi:10.1186/1742-7622-2-5 · Cited by 76 · see citing works
Goubar, A., Ades, A. E., Angelis, D. D., McGarrigle, C. A., Mercer, C. H., Tookey, P. A., Fenton, K. A., & Gill, O. N. (2008) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/j.1467-985x.2007.00537.x · Cited by 72 · see citing works
Wilks, D. C., Sharp, S. J., Ekelund, U., Thompson, S. G., Mander, A., Turner, R., Jebb, S. A., & Lindroos, A. K. (2011) · PLoS ONE · doi:10.1371/journal.pone.0017205 · Cited by 71 · see citing works
Finucane, M. M., Samet, J. H., & Horton, N. J. (2007) · Epidemiologic Perspectives & Innovations · doi:10.1186/1742-5573-4-8 · Cited by 71 · see citing works
Bias Analysis for Uncontrolled Confounding in the Health Sciences
Arah, O. A. (2015) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-032315-021644 · Cited by 69 · see citing works
Uncertainties in estimating health risks associated with exposure to ionising radiation
Preston, R. J., Boice, J. D., Brill, A. B., Chakraborty, R., Conolly, R. B., Hoffman, F. O., Hornung, R., Kocher, D. C., Land, C. E., Shore, R. E., et al. (2013) · Journal of Radiological Protection · doi:10.1088/0952-4746/33/3/573 · Cited by 69 · see citing works
Greenland, S., & Gustafson, P. (2006) · American Journal of Epidemiology · doi:10.1093/aje/kwj155 · Cited by 67 · see citing works
Momoli, F., Siemiatycki, J., McBride, M. L., Parent, M., Richardson, L., Bedard, D., Platt, R., Vrijheid, M., Cardis, E., & Krewski, D. R. (2017) · American Journal of Epidemiology · doi:10.1093/aje/kwx157 · Cited by 66 · see citing works
Is Probabilistic Bias Analysis Approximately Bayesian?
MacLehose, R. F., & Gustafson, P. (2011) · Epidemiology · doi:10.1097/ede.0b013e31823b539c · Cited by 65 · see citing works
Jones, H. E., Hickman, M., Kasprzyk‐Hordern, B., Welton, N. J., Baker, D. R., & Ades, A. E. (2014) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2014.02.101 · Cited by 65 · see citing works
New insights in the link between malocclusion and periodontal disease
Bernhardt, O., Krey, K., Daboul, A., Völzke, H., Kindler, S., Kocher, T., & Schwahn, C. (2019) · Journal Of Clinical Periodontology · doi:10.1111/jcpe.13062 · Cited by 65 · see citing works
Setting a standard for electricity pilot studies
Davis, A. L., Krishnamurti, T., Fischhoff, B., & de Bruin, W. B. (2013) · Energy Policy · doi:10.1016/j.enpol.2013.07.093 · Cited by 65 · see citing works
Turner, R., Lloyd-Jones, M., Anumba, D. O. C., Smith, G. C. S., Spiegelhalter, D. J., Squires, H., Stevens, J., Sweeting, M. J., Urbaniak, S. J., Webster, R., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0030711 · Cited by 63 · see citing works
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Greenland, S. (2009) · Statistical Science · doi:10.1214/09-sts291 · Cited by 63 · see citing works
On the Nondifferential Misclassification of a Binary Confounder
Ogburn, E., & VanderWeele, T. (2012) · Epidemiology · doi:10.1097/ede.0b013e31824d1f63 · Cited by 67 · see citing works
What are the Most Important Statistical Ideas of the Past 50 Years?
Gelman, A., & Vehtari, A. (2021) · Journal of the American Statistical Association · doi:10.1080/01621459.2021.1938081 · Cited by 60 · see citing works
Bayesian Methods for Correcting Misclassification
MacLehose, R. F., Olshan, A. F., Herring, A. H., Honein, M. A., Shaw, G. M., & Romitti, P. A. (2008) · Epidemiology · doi:10.1097/ede.0b013e31818ab3b0 · Cited by 61 · see citing works
- Authors
- Greenland, S.
- Affiliations
- University of California, Los Angeles (US)
- Corresponding author
- Greenland, Sander
- ORCID
- Greenland, Sander
- Venue
- Journal of the Royal Statistical Society Series A (Statistics in Society)
- Publisher
- Oxford University Press (OUP)
- Published
- 2005-03-01
- Volume
- 168
- Issue
- 2
- Pages
- 267-306
- ISSN
- 0964-1998 (ISSN-L)
- 1467-985X
- OpenAlex
- W2144802852
- Cited by
- 497
- References
- 132
- Citations by year
- 2026: 7 · 2025: 23 · 2024: 15 · 2023: 11 · 2022: 16 · 2021: 32 · 2020: 24 · 2019: 14 · 2018: 19 · 2017: 25 · 2016: 23 · 2015: 23 · 2014: 23 · 2013: 29 · 2012: 21
- FWCI
- 39.11
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Journal of the Royal Statistical Society Series A (Statistics in Society) (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Keywords
- bias parameter, sensitivity analysis, Bayesian analysis, case-control study, residential magnetic field exposure, pediatric leukemia, pooled analysis, meta-analysis, research planning
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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