The DOI matches its Crossref record; 99 of the 108 references it cites were found in a registry or an index.
Confounding and Collapsibility in Causal Inference
Open accessAbstract
Consideration of confounding is fundamental to the design and analysis of studies of causal effects. Yet, apart from confounding in experimental designs, the topic is given little or no discussion in most statistics texts. We here provide an overview of confounding and related concepts based on a counterfactual model for causation. Special attention is given to definitions of confounding, problems in control of confounding, the relation of confounding to exchangeability and collapsibility, and the importance of distinguishing confounding from noncollapsibility.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Both models account for potential biases and confounding factors [20, 21].”
From Health and Socio-Economic Impacts of Climate-Related Displacement in Bangladesh’s Chars: Causal Evidence From a Household Survey (2026) · cites this paper as [20]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“The causal interpretation of the estimated treatment effects relies on the standard identification assumptions used in the program-evaluation literature [16, 20, 21].”
From Health and Socio-Economic Impacts of Climate-Related Displacement in Bangladesh’s Chars: Causal Evidence From a Household Survey (2026) · cites this paper as [20]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The central role of the propensity score in observational studies for causal effects
ROSENBAUM, P. R., & RUBIN, D. B. (1983) · Biometrika · doi:10.1093/biomet/70.1.41 · Cited by 31,241
Specification Tests in Econometrics
Hausman, J. A. (1978) · Econometrica · doi:10.2307/1913827 · Cited by 18,820
Hume, D. A. (1739) · Cambridge University Press eBooks · doi:10.1017/cbo9780511620409.040 · Cited by 9,910
The Statistical Analysis of Failure Time Data.
Aitkin, M. A., Kalbfleisch, J. D., & Prentice, R. L. (1981) · Biometrics · doi:10.2307/2530581 · Cited by 9,875
Estimating causal effects of treatments in randomized and nonrandomized studies
Rubin, D. B. (1974) · Journal of Educational Psychology · doi:10.1037/h0037350 · Cited by 9,436
Statistics and Causal Inference
Holland, P. W. (1986) · Journal of the American Statistical Association · doi:10.1080/01621459.1986.10478354 · Cited by 5,293
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
Fisher, R. A. (1936) · BMJ · doi:10.1136/bmj.1.3923.554-a · Cited by 4,980
Causal Diagrams for Epidemiologic Research
Greenland, S., Pearl, J., & Robins, J. M. (1999) · Epidemiology · doi:10.1097/00001648-199901000-00008 · Cited by 3,728
Self-citationAir 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 3,045
Lauritzen, S. L. (1996) · doi:10.1093/oso/9780198522195.001.0001 · Cited by 2,976
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
Robins, J. (1986) · Mathematical Modelling · doi:10.1016/0270-0255(86)90088-6 · Cited by 2,451
Self-citationCausal diagrams for empirical research
PEARL, J. (1995) · Biometrika · doi:10.1093/biomet/82.4.669 · Cited by 2,355 · cited 3×
“…for Y of the system of equations when X is “set” to xk; a change from x0 to xk has no effect if X does not appear in the system, or more generally, if the solution is the same regardless of whether X is set to x0 or xk (Balke and Pearl, 1994; Robins, 1995a; Pearl, 1995; Galles and Pearl, 1998).”
BackgroundMethodSelf-citationThe interpretation of interaction in contingency tables
Simpson, E. H. (1951) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1951.tb00088.x · Cited by 2,301 · cited 1×
“Noncollapsibility (violation of collapsibility) is sometimes referred to as Simpson’s paradox, after a celebrated article by Simpson (1951).”
BackgroundStalnaker, R. C. (1968) · IFS · doi:10.1007/978-94-009-9117-0_2 · Cited by 2,220
Statistical Methods for Comparing Regression Coefficients Between Models
Clogg, C. C., Petkova, E., & Haritou, A. (1995) · American Journal of Sociology · doi:10.1086/230638 · Cited by 2,075
Graphical Models in Applied Multivariate Statistics
Goodall, C. R., & Whittaker, J. (1991) · Technometrics · doi:10.2307/1269424 · Cited by 1,842
Identifiability and exchangeability for direct and indirect effects
Robins, J. M., & Greenland, S. (1992) · Epidemiology · doi:10.1097/00001648-199203000-00013 · Cited by 1,793
Self-citationAn Enquiry concerning Human Understanding
Hume, D. A. (1748) · Oxford University Press eBooks · doi:10.1093/oseo/instance.00032980 · Cited by 1,606
A System of Logic, Ratiocinative and Inductive
Mill, J. S. (2023) · Routledge eBooks · doi:10.4324/9781003009450-5 · Cited by 1,430
- Statistical Models for Epidemiology
Broemeling, L. D. (2013) · Chapman & Hall/CRC eBooks · doi:10.1201/b15382-9 · Cited by 1,346
Methods in Observational Epidemiology
Kelsey, J. L. (1986) · Cited by 1,307
(1958) · Medical Entomology and Zoology · Cited by 1,059
Heckman, J. J., & Hotz, V. J. (1989) · Journal of the American Statistical Association · doi:10.2307/2290059 · Cited by 969
Components of a Difference Between Two Rates
Kitagawa, E. M. (1955) · Journal of the American Statistical Association · doi:10.1080/01621459.1955.10501299 · Cited by 901
Heckman, J. J. (1989) · National Bureau of Economic Research · doi:10.3386/w2861 · Cited by 892
Correlated Binary Regression with Covariates Specific to Each Binary Observation
Prentice, R. L. (1988) · Biometrics · doi:10.2307/2531733 · Cited by 861
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 850
Estimation, Inference and Specification Analysis
White, H. (1994) · Cambridge University Press eBooks · doi:10.1017/ccol0521252806 · Cited by 736
Rothman, K. J. (1988) · Cited by 690
Identifiability, Exchangeability, and Epidemiological Confounding
GREENLAND, S., & ROBINS, J. M. (1986) · International Journal of Epidemiology · doi:10.1093/ije/15.3.413 · Cited by 686
Self-citationGail, M. H., Wieand, S., & Piantadosi, S. (1984) · Biometrika · doi:10.1093/biomet/71.3.431 · Cited by 683
Discrete Multivariate Analysis Theory and Practice
Bishop, Y. M. M., Fienberg, S. E., & Holland, P. W. (2007) · Springer eBooks · doi:10.1007/978-0-387-72806-3 · Cited by 678
Rubin, D. B. (1990) · Statistical Science · doi:10.1214/ss/1177012032 · Cited by 665
Neuhaus, J. M., Kalbfleisch, J. D., & Hauck, W. W. (1991) · International Statistical Review · doi:10.2307/1403572 · Cited by 547
INTERPRETATION AND CHOICE OF EFFECT MEASURES IN EPIDEMIOLOGIC ANALYSES1
Greenland, S. (1987) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a114593 · Cited by 546
Self-citationCausal Inference from Complex Longitudinal Data
Robins, J. M. (1997) · Lecture Notes in Statistics · doi:10.1007/978-1-4612-1842-5_4 · Cited by 510
Self-citationNOTES ON THE THEORY OF ASSOCIATION OF ATTRIBUTES IN STATISTICS
Yule, G. U. (1903) · Biometrika · doi:10.1093/biomet/2.2.121 · Cited by 466
CONCEPTUAL PROBLEMS IN THE DEFINITION AND INTERPRETATION OF ATTRIBUTABLE FRACTIONS
Greenland, S., & Robins, J. M. (1988) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a115073 · Cited by 420
Self-citationSome Surprising Results about Covariate Adjustment in Logistic Regression Models
Robinson, L. D., & Jewell, N. P. (1991) · International Statistical Review · doi:10.2307/1403444 · Cited by 410
Correlations Genuine and Spurious in Pearson and Yule
Aldrich, J. (1995) · Statistical Science · doi:10.1214/ss/1177009870 · Cited by 401
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
Randomization, Statistics, and Causal Inference
Greenland, S. (1990) · Epidemiology · doi:10.1097/00001648-199011000-00003 · Cited by 385
Self-citationRobins, 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
Self-citationCONFOUNDING: ESSENCE AND DETECTION1
Miettinen, O. S., & Cook, E. F. (1981) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a113225 · Cited by 350
Rosenbaum, P. R. (1995) · Springer series in statistics · doi:10.1007/978-1-4757-2443-1 · Cited by 349
Causal Inference without Counterfactuals
Dawid, A. P. (2001) · Applied logic series · doi:10.1007/978-94-017-1586-7_3 · Cited by 343
Robins, J. (1987) · Journal of Chronic Diseases · doi:10.1016/s0021-9681(87)80018-8 · Cited by 305
Self-citationDart, T. (1955) · Medical Entomology and Zoology · Cited by 292
Covariate imbalance and random allocation in clinical trials
Senn, S. J. (1989) · Statistics in Medicine · doi:10.1002/sim.4780080410 · Cited by 281
Causal Inference in Infectious Diseases
Halloran, M. E., & Struchiner, C. J. (1995) · Epidemiology · doi:10.1097/00001648-199503000-00010 · Cited by 263
Robins, J. M. (1987) · Computers & Mathematics with Applications · doi:10.1016/0898-1221(87)90238-0 · Cited by 213
Self-citationRubin, D. B. (2006) · Cambridge University Press eBooks · doi:10.1017/cbo9780511810725.033 · Cited by 211
Rubin, D. B. (1991) · Biometrics · doi:10.2307/2532381 · Cited by 203
THE ROLE OF MODEL SELECTION IN CAUSAL INFERENCE FROM NONEXPERIMENTAL DATA
Robins, J. M., & Greenland, S. (1986) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a114254 · Cited by 201
Self-citationAn axiomatic characterization of causal counterfactuals
Galles, D., & Pearl, J. (1998) · Foundations of Science · doi:10.1023/a:1009602825894 · Cited by 192
Self-citationCollapsibility of Multidimensional Contingency Tables
Whittemore, A. S. (1978) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1978.tb01046.x · Cited by 189
Robins, J. M., & Greenland, S. (1994) · Journal of the American Statistical Association · doi:10.1080/01621459.1994.10476807 · Cited by 181
Self-citationCounterfactual Probabilities: Computational Methods, Bounds and Applications
Balke, A., & Pearl, J. (1994) · Elsevier eBooks · doi:10.1016/b978-1-55860-332-5.50011-0 · Cited by 175
Self-citationGraphical models in applied multivariate statistics
Whittaker, J. (1991) · Cited by 174
COMPONENTS OF THE CRUDE RISK RATIO
Miettinen, O. S. (1972) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a121443 · Cited by 169
The concept of residual confounding in regression models and some applications
Becher, H. (1992) · Statistics in Medicine · doi:10.1002/sim.4780111308 · Cited by 168
Correction for non-compliance in equivalence trials
Robins, J. M. (1998) · Statistics in Medicine · doi:10.1002/(sici)1097-0258(19980215)17:3 · Cited by 167
Self-citationThe Probability of Causation under a Stochastic Model for Individual Risk
Robins, J. M., & Greenland, S. (1989) · Biometrics · doi:10.2307/2531765 · Cited by 165
Self-citationCausal Inference in the Social and Behavioral Sciences
Sobel, M. E. (1995) · Springer eBooks · doi:10.1007/978-1-4899-1292-3_1 · Cited by 164
PRODAN, M. (1968) · Elsevier eBooks · doi:10.1016/b978-0-08-012441-4.50022-5 · Cited by 164
Simon, H. A., & Rescher, N. (1966) · Philosophy of Science · doi:10.1086/288105 · Cited by 157
Collapsibility and response variables in contingency tables
Asmussen, S., & Edwards, D. (1983) · Biometrika · doi:10.1093/biomet/70.3.567 · Cited by 148
Pertinency of an extraneous variable
Bross, I. D. J. (1967) · Journal of Chronic Diseases · doi:10.1016/0021-9681(67)90080-x · Cited by 118
Statistical Methods for Analyzing Collapsibility in Regression Models
Clogg, C. C., Petkova, E., & Shihadeh, E. S. (1992) · Journal of Educational Statistics · doi:10.3102/10769986017001051 · Cited by 116
An Introduction to Logic and Scientific Method
COHEN, M. R., & NAGEL, E. (1943) · Andalas University Repository (Andalas University) · Cited by 114
Latent Variable Modeling and Applications to Causality
Berkane, M. (1997) · Lecture notes in statistics · doi:10.1007/978-1-4612-1842-5 · Cited by 110
Marginalization and Collapsibility in Graphical Interaction Models
Frydenberg, M. (1990) · The Annals of Statistics · doi:10.1214/aos/1176347626 · Cited by 96
Recent methodological contributions to clinical trials.
Cornfield, J. (1976) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a112313 · Cited by 96
Confidence intervals for causal parameters
Robins, J. M. W. (1988) · Statistics in Medicine · doi:10.1002/sim.4780070707 · Cited by 91
Self-citationThe Assumptions on Which Causal Inferences Rest
Stone, R. (1993) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1993.tb01915.x · Cited by 86
A consequence of omitted covariates when estimating odds ratios
Hauck, W. W., Neuhaus, J. M., Kalbfleisch, J. D., & Anderson, S. (1991) · Journal of Clinical Epidemiology · doi:10.1016/0895-4356(91)90203-l · Cited by 83
Wermuth, N. (1987) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1987.tb01706.x · Cited by 75
EFFECTS OF COVARIATE OMISSION AND CATEGORIZATION WHEN ANALYSING RANDOMIZED TRIALS WITH THE COX MODEL
Schmoor, C., & Schumacher, M. C. (1997) · Statistics in Medicine · doi:10.1002/(sici)1097-0258(19970215)16:3 · Cited by 73
The foundations of confounding in epidemiology
Robins, J. M., & Morgenstern, H. (1987) · Computers & Mathematics with Applications · doi:10.1016/0898-1221(87)90236-7 · Cited by 69
Self-citationThe causes of human variability.
Fisher, R. A. (1919) · PubMed · Cited by 67
CHOOSING THE PARAMETER FOR A 2 × 2 TABLE OR A 2 × 2 × 2 TABLE ANALYSIS
Hamilton, M. A. (1979) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a112689 · Cited by 65
Causal Inference Without Counterfactuals
Dawid, A. P. (2000) · Journal of the American Statistical Association · doi:10.2307/2669377 · Cited by 61
An analytic method for randomized trials with informative censoring: Part 1
Robins, J. M. (1995) · Lifetime Data Analysis · doi:10.1007/bf00985759 · Cited by 60
Self-citationTesting Collapsibility in Contingency Tables
Ducharme, G. R., & Lepage, Y. (1986) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1986.tb01402.x · Cited by 60
Collapsibility of Logistic Regression Coefficients
Guo, J., & Geng, Z. (1995) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1995.tb02029.x · Cited by 58
How Dependent Causes of Death Can Make Risk Factors Appear Protective
SLUD, E. V., & Byar, D. P. (1988) · Biometrics · doi:10.2307/2531915 · Cited by 58
Collapsibility of Relative Risk in Contingency Tables with a Response Variable
Geng, Z. (1992) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1992.tb01898.x · Cited by 57
Confounding in Epidemiologic Studies: The Adequacy of the Control Group as a Measure of Confounding
WICKRAMARATNE, P. J., & Holford, T. R. (1987) · Biometrics · doi:10.2307/2531530 · Cited by 56
Randomization models for the matched and unmatched 2 × 2 tables
Copas, J. B. (1973) · Biometrika · doi:10.1093/biomet/60.3.467 · Cited by 54
Moderating Effects of Subgroups in Linear Models
Wermuth, N. (1989) · Biometrika · doi:10.1093/biomet/76.1.81 · Cited by 38
American Marriage and Family Relationships.
H., A. B., Groves, E. R., & Ogburn, W. R. (1929) · Journal Of The Royal Statistical Society · doi:10.2307/2341515 · Cited by 37
Algorithm AS 244: Decomposability and Collapsibility for Log-Linear Models
Geng, Z. (1989) · Journal of the Royal Statistical Society Series C (Applied Statistics) · doi:10.2307/2347694 · Cited by 28
Greenland, S., & Mickey, R. M. (1988) · Journal of the Royal Statistical Society Series C (Applied Statistics) · doi:10.2307/2347308 · Cited by 27
Self-citationEpidemiology of vaginal adenosis and adenocarcinoma associated with exposure to stilbestrolin utero
Poskanzer, D. C., & Herbst, A. L. (1977) · Cancer · doi:10.1002/1097-0142(197704)39:4+ · Cited by 26
Dependent competing risks and the latent-failure model.
Ev, S., Byar, D. P., & Schatzkin, A. G. (1988) · PubMed · Cited by 21
Causal diagrams for empirical research
Robins, J. M. (1995) · Biometrika · doi:10.1093/biomet/82.4.695 · Cited by 13
Self-citationOn the Identification of Nonparametric Structural Models
Pearl, J. (1997) · Lecture notes in statistics · doi:10.1007/978-1-4612-1842-5_3 · Cited by 9
Self-citation
Flagged first, then by citations
9 of the 108 references couldn’t be matched to a known paper.
Research works printed but not linked: 9
- Clayton, D. and Hills, M. (1993). Statistical Models in Epidemiology. Oxford Univ. Press.
- Feynman, R. P. (1963). Lectures on Physics. Addison-Wesley, Reading, MA.
- Gail, M. H. (1986). Adjusting for covariates that have the same distribution in exposed and unexposed cohorts. In Modern Statistical Methods in Chronic Disease Epidemiology (S. H. Moolgavkar, and R. L. Prentice, eds.) 3-18. Wiley, New York.
- MacMahon, B. and Pugh, T. F. (1967). Causes and entities of disease. In Preventive Medicine (D. W. Clark and B. MacMahon, eds.) 11-18. Little Brown, Boston.
- McKechnie, J. L. (ed.) (1979). Webster's New Twentieth Century Dictionary. Simon and Schuster, New York.
- Neyman, J. (1935). Statistical problems in agricultural experimentation (with discussion). J. Roy. Statist. Soc. Suppl. 2 107-180. · DOI
- Pearl, J. and Robins, J. M. (1995). Probabilitic evaluation of sequential plans from causal model with hidden variables. In Uncertainty in Artificial Intelligence (P. Besnard and S. Hanks, eds.) 11 444-453. Morgan-Kaufman, San Francisco.
- Robins, J. M. (1998). Correction for non-compliance in equivalence trials. Statistics in Medicine 17 269-302. · DOI
- Rothman, K. J. and Greenland, S. (1998). Modern Epidemiology, 2nd ed. Lippincott-Raven, Philadelphia.
Cited by
Sorted by citations
Matching Methods for Causal Inference: A Review and a Look Forward
Stuart, E. A. (2010) · Statistical Science · doi:10.1214/09-sts313 · Cited by 5,478
Mediation Analysis: A Practitioner's Guide
VanderWeele, T. J. (2016) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-032315-021402 · Cited by 1,985
“…the correct causal structure ov i it y A cce B = γλ γ + λ − . can alter the direct and indirect effects) we can take our direct and indirect effects estimates and their confidence intervals from the observed data and divide the direct effect estimate and both limits of its confidence interval by…”
BackgroundA review of instrumental variable estimators for Mendelian randomization
Burgess, S., Small, D. S., & Thompson, S. G. (2015) · Statistical Methods in Medical Research · doi:10.1177/0962280215597579 · Cited by 1,769
“Noncollapsibility is the violation of this property.(62) The relative risk and absolute risk difference are collapsible measures of association.”
BackgroundMoons, K. G. M., Wolff, R. F., Riley, R. D., Whiting, P. F., Westwood, M., Collins, G. S., Reitsma, J. B., Kleijnen, J., & Mallett, S. (2019) · Annals of Internal Medicine · doi:10.7326/m18-1377 · Cited by 1,669
Hernan, M. A. (2002) · American Journal of Epidemiology · doi:10.1093/aje/155.2.176 · Cited by 1,445
Metadata
- Authors
- Greenland, S., Pearl, J., & Robins, J. M.
- Venue
- Statistical Science
- Publisher
- Institute of Mathematical Statistics
- Published
- 1999-02-01
- Volume
- 14
- Issue
- 1
- Pages
- 29-46
- ISSN
- 0883-4237 (ISSN-L)
- 2168-8745
- OpenAlex
- W1996016456
- Cited by
- 933
- References
- 108
- Citations by year
- 2026: 43 · 2025: 47 · 2024: 61 · 2023: 53 · 2022: 65 · 2021: 75 · 2020: 48 · 2019: 40 · 2018: 40 · 2017: 36 · 2016: 35 · 2015: 44 · 2014: 52 · 2013: 47 · 2012: 47
- FWCI
- 13.67
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Statistical Science (publishedVersion)
- Project Euclid (Cornell University) (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy of Biology and Scientific Explanation
- Keywords
- confounding, collapsibility, counterfactual modeling, causal inference, exchangeability, causal effects, observational studies
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 ›
Are you an author, or do you see a problem with this page? Request a review
