The DOI matches its Crossref record; 28 of the 30 references it cites were found in a registry or an index.
The Table 2 Fallacy: Presenting and Interpreting Confounder and Modifier Coefficients
Open accessAbstract
It is common to present multiple adjusted effect estimates from a single model in a single table. For example, a table might show odds ratios for one or more exposures and also for several confounders from a single logistic regression. This can lead to mistaken interpretations of these estimates. We use causal diagrams to display the sources of the problems. Presentation of exposure and confounder effect estimates from a single model may lead to several interpretative difficulties, inviting confusion of direct-effect estimates with total-effect estimates for covariates in the model. These effect estimates may also be confounded even though the effect estimate for the main exposure is not confounded. Interpretation of these effect estimates is further complicated by heterogeneity (variation, modification) of the exposure effect measure across covariate levels. We offer suggestions to limit potential misunderstandings when multiple effect estimates are presented, including precise distinction between total and direct effect measures from a single model, and use of multiple models tailored to yield total-effect estimates for covariates.
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
“After controlling for gender and age as potential confounding factors, independent associations between the outcome variables of burnout as well as anxiety/depression and the explanatory variables (i.e., ALTs, psychological flexibility) were examined [58].”
From The mediating role of psychological flexibility in the association of autistic-like traits with burnout and depression in medical students during clinical clerkships in Japan: a university-based cross-sectional study (2023) · cites this paper as [58]
Experimental — accuracy not yet measured
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 Elements of Statistical Learning
Hastie, T., Tibshirani, R., & Friedman, J. (2009) · Springer Series in Statistics · doi:10.1007/978-0-387-84858-7 · Cited by 25,970
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
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 3,045
Causal diagrams for empirical research
PEARL, J. (1995) · Biometrika · doi:10.1093/biomet/82.4.669 · Cited by 2,355 · cited 1×
“Model 1 then remains valid for obtaining an unbiased estimate of the total effect of HIV on the log odds of stroke; that is, under model 1, β1 retains its interpretation as the total effect of HIV, as it did under Figure 1, because smoking and age satisfy the back-door criterion for sufficiency for confounding control…”
BackgroundIdentifiability 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-citationHernan, M. A. (2002) · American Journal of Epidemiology · doi:10.1093/aje/155.2.176 · Cited by 1,445
Statistical modeling: The two cultures
Breiman, L. (2001) · Cited by 1,314
Dose-Response and Trend Analysis in Epidemiology
Greenland, S. (1995) · Epidemiology · doi:10.1097/00001648-199507000-00005 · Cited by 1,086
Self-citationConfounding and Collapsibility in Causal Inference
Greenland, S., Pearl, J., & Robins, J. M. (1999) · Statistical Science · doi:10.1214/ss/1009211805 · Cited by 933 · cited 3×
“represent changes in the log odds of the outcome) and we assume the outcome is uncommon at all covariate levels to avoid complications arising from noncollapsibility of odds ratios (9, 10).”
BackgroundSelf-citationQuantifying Biases in Causal Models: Classical Confounding vs Collider-Stratification Bias
Greenland, S. (2003) · Epidemiology · doi:10.1097/01.ede.0000042804.12056.6c · Cited by 810
Self-citation
Flagged first, then by citations
2 of the 30 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Items 801–900 of 1,000
Identifying high school smokers likely to persist in smoking at age 31
Wellman, R. J., Dugas, E. N., Sylvestre, M., & O’Loughlin, J. L. (2023) · Addictive Behaviors · doi:10.1016/j.addbeh.2023.107720 · Cited by 1
Szilcz, M., Wastesson, J. W., Calderón‐Larrañaga, A., Morin, L., Lindman, H., & Johnell, K. (2023) · Frontiers in Oncology · doi:10.3389/fonc.2023.1223563 · Cited by 1
Wellman, R. J., O’Loughlin, E. K., Maximova, K., Kalubi, J., Riglea, T., & O’Loughlin, J. L. (2024) · Health Promotion and Chronic Disease Prevention in Canada · doi:10.24095/hpcdp.44.4.03 · Cited by 1
“We did not estimate a model containing all potential correlates, as such models may include variables on the causal pathway for the correlate of interest, 23 which can result in attenuated estimates.”
BackgroundHardiman, S., Fradet, G. J., Kuramoto, L., Law, M. R., Robinson, S. D., & Sobolev, B. G. (2024) · JTCVS Open · doi:10.1016/j.xjon.2024.04.009 · Cited by 1
Major‐Smith, D., Morgan, J., Halstead, I. N., Tohidinik, H. R., Goulding, N., Iles‐Caven, Y., Golding, J., & Northstone, K. (2024) · Wellcome Open Research · doi:10.12688/wellcomeopenres.18517.3 · Cited by 1
“…bidirectional), then these variables may also be mediators of the relationship between RSBB and some outcome of interest, meaning that adjusting for said covariate would bias the intended causal effect (6,8,33; for a more detailed discussion of this in relation to RSBB, see the discussion of 14).”
Associations between flood risk and US Census tract–level health outcomes
Sheng, A., Reich, B. J., & Messier, K. P. (2024) · American Journal of Epidemiology · doi:10.1093/aje/kwae093 · Cited by 1
Abe, H., Tanaka, S., Sakaguchi, H., Ueda, C., Hori, H., Nakai, T., Yoshizaki, T., Kawara, F., Toyonaga, T., Kinoshita, M., et al. (2024) · Digestive Endoscopy · doi:10.1111/den.14909 · Cited by 1
He, Z., Wei, J.-T., Jiang, H.-M., Wang, J.-Y., Lai, J.-Y., Li, S., Chen, Z., & Luo, Q. (2024) · Journal of Pain Research · doi:10.2147/jpr.s480910 · Cited by 1
“28 To eliminate the potential influence of individuals without OA on the results, we conducted a sensitivity analysis by excluding participants without pain or OA, then reconstructed the pain trajectories and identified the predictors.”
MethodEchoes from the trenches: World War I deaths and contemporary support for the far-right in France
Surdea‐Hernea, V. (2024) · European Political Science Review · doi:10.1017/s1755773924000195 · Cited by 1
Fleming, V. H., Xu, J., Chen, X., Hall, D. B., & Southwood, R. L. (2024) · Journal of Pharmacy Technology · doi:10.1177/87551225241303848 · Cited by 1
“This approach follows work of Westreich and Greenland 30 and others 31 who argue that such effects can remain confounded and are not amenable to straight-forward interpretation.”
Causal Reasoning and Inference in Epidemiology
Didelez, V. (2024) · Springer eBooks · doi:10.1007/978-1-4614-6625-3_74-1 · Cited by 1
Ujah, O. I., Adaji, O. C., Ujah, I. A. O., & Kirby, R. S. (2025) · PLoS ONE · doi:10.1371/journal.pone.0316381 · Cited by 3
“Therefore, together with the exploratory approach employed to identify ecological correlates of ECD, it is important to interpret the effect estimates from the model outputs as mutually adjusted associations rather than as causal relationships to avoid the " Table 2 fallacy ” [58].”
Haricharan, P. B., Feine, J. S., Juwara, L., & de Souza, R. F. (2025) · Journal of Dentistry · doi:10.1016/j.jdent.2025.105720 · Cited by 1
Disparities in perceived general health of stroke survivors in the United States
Hejazian, S. S., Sadr, A. V., Vemuri, A. K., Abedi, V., & Zand, R. (2025) · Journal of the Neurological Sciences · doi:10.1016/j.jns.2025.123556 · Cited by 1
Pasco, C., Liu, Y., Zhou, J., Gough, E. K., Onzia, A. A., Parkes-Ratanshi, R. M., Melendez, J. H., Kyambadde, P., Manabe, Y. C., & Hamill, M. M. (2025) · BMC Infectious Diseases · doi:10.1186/s12879-025-11196-8 · Cited by 1
“To minimize Table 2 bias [21], a separate multivariable model was fitted for each risk factor of interest, with covariates selected a priori based on subject matter knowledge and existing literature.”
Beetsma, R. M. W. J., & Nicoli, F. (2025) · Regulation & Governance · doi:10.1111/rego.70045 · Cited by 1
Time Trends and Predictors of Gout Remission Over 6 Years
Tabi‐Amponsah, A. D., Stewart, S., Gamble, G. D., Stamp, L. K., Taylor, W. J., & Dalbeth, N. (2025) · Arthritis Care & Research · doi:10.1002/acr.25584 · Cited by 1
“19 Although we care-fully selected the variables and interpreted the results within the broader context, including the univariable analyses provided in the supplementary materials, we acknowledge that residual confounding may still be a concern.”
Richard, V., Lorthe, E., Dumont, R., Loizeau, A., Baysson, H., Zaballa, M.-E., Lamour, J., Nehme, M., Barbe, R., Posfay-Barbe, K. M., et al. (2025) · Swiss Medical Weekly · doi:10.57187/s.4247 · Cited by 1
Carrier, F. M., Trottier, H., Soucy-Proulx, M., Joosten, A., McCluskey, S. A., Luzzi, C. A., Ghai, P., Papamihali, K., Karvellas, C. J., Larbi, S., et al. (2025) · Liver Transplantation · doi:10.1097/lvt.0000000000000684 · Cited by 1
Losciale, J. M., Le, C. Y., Truong, L. K., Bullock, G. S., Mitchell, C. J., Hunt, M. A., & Whittaker, J. L. (2025) · Sports Health A Multidisciplinary Approach · doi:10.1177/19417381251352524 · Cited by 1
Education research: Getting started
Terry, J., Le, L. J., Jones, R., Sergeant, J. C., Dunham, B., & Jones, E. M. (2025) · Teaching Statistics · doi:10.1111/test.70008 · Cited by 1
“Beware of the “ Table 2 Fallacy ” , 49 where confounders and modifiers are misinterpreted in complex models, and prioritize quantifying relationships (e.g., effect sizes) and their precision (e.g., confidence intervals) over pursuing p -values.”
Ahmad, H., Forrest, A. D., & Rotenberg, M. (2025) · International Journal of Social Psychiatry · doi:10.1177/00207640251353689 · Cited by 1
“For instance, some studies adjusted for ethnicity, immigration status or racialised groups but did not focus on these as primary exposures (Westreich & Greenland, 2013).”
Ojasanya, R. A., Weese, J. S., Sobkowich, K. E., Deckert, A., Szlosek, D. A., Plum, A., Bernardo, T. M., & Poljak, Z. (2025) · Preventive Veterinary Medicine · doi:10.1016/j.prevetmed.2025.106684 · Cited by 1
Narita, Z. C. (2025) · Neuropsychopharmacology Reports · doi:10.1002/npr2.70057 · Cited by 1
Paepe, A. L. D., Gibby, A., Lisboa, L. O., Ehrhardt, B., Nunes, M. A., Fisher, E., Keogh, E., Eccleston, C., Woolley, C. S. C., McBeth, J., et al. (2025) · Pain · doi:10.1097/j.pain.0000000000003833 · Cited by 1
“6,8,19,54,55 Instead, they argue for an explicit and transparent thinking about causality to avoid these mistakes.”
Graves, E., Schacht, C. D., Gong, W., Rompaey, S. V., Alvim, M. F. S., Claquin, G., Shepherd, B. E., Green, A. F., Tique, J. A., José, E., et al. (2025) · AIDS Research and Human Retroviruses · doi:10.1177/08892229251388415 · Cited by 1
“ART, antiretroviral therapy; CASG, community adherence support group; HF, health facility; IQR, interquartile range; SMS, short message service.”
Deynu, M., Dunham, A., Nutor, J. J., & Santos, G. (2025) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2025.112960 · Cited by 1
“The separate modelling approach ensured we avoided reporting effect estimates for the exposure (independent variables) and covariates of interest from the same model, which may be misleading and result in incorrect interpretations (Bandoli et al., 2018; Westreich and Greenland, 2013).”
Deynu, M., & Nutor, J. J. (2025) · BMC Public Health · doi:10.1186/s12889-025-25303-6 · Cited by 1
“This approach was adopted to avoid reporting effect estimates for both primary exposures and other covariates from the same statistical model which may be mis-leading and resulting in incorrect interpretations [42, 43].”
Social bonds decrease epigenetic age in male bottlenose dolphins
Gerber, L., Peters, K. J., King, S. L., Allen, S. J., Connor, R. C., Forbes, O., Holmes, K. G., Kearns, A. M., Willems, E. P., Krützen, M., et al. (2025) · Communications Biology · doi:10.1038/s42003-025-09227-w · Cited by 2
Powell, C., Day, C. N., Wigle, D. A., & Habermann, E. B. (2025) · European Journal of Cardio-Thoracic Surgery · doi:10.1093/ejcts/ezaf431 · Cited by 1
Factors associated with lower-risk cannabis use in adults in their mid-thirties
Dubé, G., O’Loughlin, J. L., Fallu, J., Huỳnh, C., & Sylvestre, M. (2025) · Journal of Cannabis Research · doi:10.1186/s42238-025-00374-9 · Cited by 1
Arning, N., Fryer, H. R., & Wilson, D. J. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2514138122 · Cited by 3
“Attention could be restricted to direct effects instead but, for nongenetic variables, direct effects can differ in direction and magnitude to total effects, a source of bias known as the Table 2 fallacy (13).”
Ren, Z., Zhao, Y., Liu, Y., Chen, C., Su, B., Liu, J., & Zheng, X. (2026) · BMJ Public Health · doi:10.1136/bmjph-2025-003038 · Cited by 1
Mansfield, R., Richards, M., Ploubidis, G. B., Henderson, M., & Patalay, P. (2026) · Social Psychiatry and Psychiatric Epidemiology · doi:10.1007/s00127-025-03041-9 · Cited by 1
Cho, N. Y., Hur, D. G., Withington, C., Ali, K., Kwon, O. J., Jafarpour, A., Benharash, P., Hameed, S. M., & Choi, J. (2026) · Annals of Surgery Open · doi:10.1097/as9.0000000000000649 · Cited by 1
“While interpreting coefficients of covariates requires caution, 17 both unadjusted and adjusted analyses did not find higher trauma activation fees among safety-net hospitals.”
Slone, J., Amorim, G., Semeere, A., Diero, L. O., Otero, L., Crabtree‐Ramírez, B., Tao, R., Duda, S. N., Musick, B. S., Yiannoutsos, C. T., et al. (2026) · American Journal of Epidemiology · doi:10.1093/aje/kwag015 · Cited by 1
Ethnic Representation, Deprivation and Seizure Outcomes in a UK Tertiary Epilepsy Clinic
Carmichael, N. S., Lai, L. Y. H., Mashuk, M. S., Lu, Y., Basilio, D. D., Pegg, E., & Mohanraj, R. (2026) · Seizure · doi:10.1016/j.seizure.2026.01.012 · Cited by 1
Jonsson, E. N., Jönsson, S., Hansson, E., & Nyberg, J. (2026) · CPT Pharmacometrics & Systems Pharmacology · doi:10.1002/psp4.70203 · Cited by 1
“This common practice of presenting conditional effects in isolation, which are then incorrectly interpreted as unconditional impacts, has been described elsewhere as the “Table 2 fallacy” [24].”
Attention-deficit/hyperactivity disorder and short sleep duration among U.S. school-aged children
Hill, M. J., Flora, S. M., Knowlden, A. P., Mahabee‐Gittens, E. M., & Merianos, A. L. (2026) · Sleep Health · doi:10.1016/j.sleh.2025.11.015 · Cited by 1
Li, P., Chen, Y., Li, Z., Liu, J., Zhang, J., 王玉柱, Guo, L., Li, Y., Hu, B., Zhu, S., et al. (2026) · Antimicrobial Resistance and Infection Control · doi:10.1186/s13756-026-01707-w · Cited by 1
“…we distinguished seven true confounders from mediator of antibiotic prophylaxis, thereby avoiding over-adjustment bias—a critical limitation of data-driven approaches like stepwise regression that risk “Table 2 Fallacy” [27] or the “black box” nature of machine learning in variable selection [28].”
Llamosas‐Falcón, L., Rehm, J. T., Lange, S., Zhu, Y., & Probst, C. (2026) · Journal of Epidemiology & Community Health · doi:10.1136/jech-2025-225325 · Cited by 1
“28 All statistical analyses were conducted in R, V.4.4.1.”
InfluentialAI and research, are we (un)consciously guilty?
Couarraze, S., Joannès, C., & Roda, P. (2026) · AI and Ethics · doi:10.1007/s43681-026-01037-y · Cited by 1
“These distinctions and the careful interpretation of results help to avoid mistaken interpretations known as “Table 2 fallacy”, referring to the erroneous interpretation of all adjusted associations as causal effects [26].”
Ragagnin, K., da Silva-Oolup, S., Yu, H., Balaji, S., Côté, P., Hogg‐Johnson, S., Murnaghan, K., & Wong, J. J. (2026) · ACR Open Rheumatology · doi:10.1002/acr2.90007 · Cited by 1
John, A., O’Nions, E., Corrigan, L., Cotton, J., Donnellan, W. J., Nimmons, D., Shelford, H., Eshetu, A., Saunders, R., Baou, C. E., et al. (2026) · Nature Mental Health · doi:10.1038/s44220-026-00600-0 · Cited by 1
Neumann, M., Schüttler, H., & Klatt, T. (2026) · Journal of Experimental Criminology · doi:10.1007/s11292-026-09741-9 · Cited by 3
Bhatnagar, T., Sindhuja, V., Swathi, S. S., Gopalakrishnan, S. N., Velayudhan, A., Siromany, V., VanderEnde, D. S., Malpiedi, P. J., Smith, R. M., Bollinger, S., et al. (2026) · Antimicrobial Resistance and Infection Control · doi:10.1186/s13756-026-01747-2 · Cited by 1
“1 software, based on literature review, biological plausibility, and contextual understanding among the study team [23, 24].”
Gonzalez, M., Castro, J. E. C., Umucu, E., & Rojas‐Alvarez, A. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1733641 · Cited by 1
A spatial approach to duet function in Adelaide's warbler, Setophaga adelaidae
Krause, S. W., Bonnell, T. R., Dostie, M. J., Booth, S. I., Mower, P. C., & Logue, D. M. (2026) · Animal Behaviour · doi:10.1016/j.anbehav.2026.123575 · Cited by 1
Trindade, L., Pereira, J., Rogero, M., Fisberg, R. M., & Sarti, F. (2026) · BMC Public Health · doi:10.1186/s12889-026-27729-y · Cited by 1
“Additionally, to prevent potential overadjustment bias and the masking of associations due to clinical collinearity among these morbidities [35], we conducted sensitivity analyses by estimating parallel separate models for each cardiometabolic risk factor, adjusting for socioeconomic, demographic,…”
Shrestha, S., & Khanal, V. (2026) · International Breastfeeding Journal · doi:10.1186/s13006-026-00860-7 · Cited by 1
“This approach was adopted to avoid 'Table 2 Fallacy' following the recommendations from available literature [41, 42].”
Elevating the importance of Risk of Bias assessment for ecology and evolutionary biology
Čulina, A., Foster, D., Grainger, M., O’Dea, R. E., Pescott, O. L., Sánchez‐Tójar, A., Boyd, R. J., Koricheva, J., Nakagawa, S., & Stewart, G. B. (2026) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.70356 · Cited by 4
“A nice example can be found in Westreich and Greenland ( 2013 ) who demonstrate how this can lead to confusion between direct-effect estimates and total-effect estimates for covariates in the model. et al. ( 1991 ) found that there was a statistically significant inter-observer effect in the…”
Hvidhjelm, J., & Berring, L. L. (2026) · Journal of Psychiatric and Mental Health Nursing · doi:10.1111/jpm.70192 · Cited by 1
Smit, F., Franco, M. R., Sherrington, C., Cullati, S., Blyth, F., van Zwieten, A., & Khalatbari‐Soltani, S. (2026) · Journal of Epidemiology & Community Health · doi:10.1136/jech-2025-225014 · Cited by 1
Fox, M. P., Wesselink, A. K., Kezios, K., Jenson, T. E., & Jimenez, M. P. (2026) · American Journal of Epidemiology · doi:10.1093/aje/kwag201 · Cited by 1
Suh, B., Cho, Y., Choi, E.-Y., Lee, H., Kang, H.-R., Kim, H., Man, K. K. C., Shin, J., & Noh, Y. (2026) · JAMA Network Open · doi:10.1001/jamanetworkopen.2026.30781 · Cited by 1
Hammadeh, B. M., Talafha, M., Al-Haddad, Z., Radi, R., Faqeeh, T. J., Hussein, A. M., & Ghanem, R. (2026) · Journal of Robotic Surgery · doi:10.1007/s11701-026-04075-0 · Cited by 1
“…a cumulative link mixed model with a university random intercept estimated adjusted associations and average marginal differences for the twelve terms, testing trust (H4) and surgical career intention (H5); a model without belief scores gave total associations of background characteristics [28 ].”
Challenges in Epidemiological and Statistical Evaluations of Effect Modifiers and Confounders
Jung, S. Y. (2014) · Frontiers in Public Health · doi:10.3389/fpubh.2014.00277 · Cited by 1
Causal models: Specification, fitting, reporting, and interpretation
Boutin, A., & Joseph, K. S. (2018) · Paediatric and Perinatal Epidemiology · doi:10.1111/ppe.12483 · Cited by 1
Mbotwa, J., de Kamps, M., Baxter, P. D., Ellison, G. T. H., & Gilthorpe, M. S. (2021) · PLoS ONE · doi:10.1371/journal.pone.0243674 · Cited by 1
Acute Effects of Blood Sugar Regulation on Endothelial Functions in Patients with Diabetes
Mammadov, G., Şimşek, E., Şimşir, İ. Y., Yağmur, B., & Çınar, C. S. (2022) · e-Journal of Cardiovascular Medicine · doi:10.32596/ejcm.galenos.2022.2022-04-027 · Cited by 1
Comparable Public Health Responses to COVID-19 Pandemic
Khan, F. S., Ullah, A., Khan, O. J., Sehar, B., Alsubaie, A. S. R., Asmat, S., & Zeb, F. (2022) · The Open Public Health Journal · doi:10.2174/18749445-v15-e2207290 · Cited by 1
Cvejic, R. C., Watkins, T. R., Walker, A. R., Reppermund, S., Srasuebkul, P., Draper, B., Withall, A., Winkler, D., Honan, I., Mackechnie, D., et al. (2022) · BMJ Open · doi:10.1136/bmjopen-2022-065982 · Cited by 1
“To determine whether inclusion of diagnoses recorded in the 365 days preceding the index admission impacted the effect estimates of variables that may be associated with transfer to RAC, we repeated the above analyses using all diagnoses received at hospital admissions occurring during the lookback…”
MethodForthal, S., Choi, S., Yerneni, R., Macinski, S., Levey, W., Kerwin, J., Ahadzi, M., Fish, D. G., Anderson, B. J., & Neighbors, C. J. (2022) · AIDS Care · doi:10.1080/09540121.2022.2158302 · Cited by 1
“Estimates for these covariates were not reported in the text because they cannot be interpreted as conditional total e ff ects with potential confounders controlled for (Westreich & Greenland, 2013).”
BackgroundIntersecting Epidemics of Many Unknowns: Human Immunodeficiency Virus and Covid-19
Tomy, A. D., & Chy, T. (2022) · Journal of Biomedicine and Biochemistry · doi:10.57238/jbb.2022.17450 · Cited by 1
“People who can protect themselves in their homes may experience more stress if they are alone in their homes, if being at home entails additional caregiving responsibilities, or if they live with a significant other who constitutes a physical or emotional threat (20,21).”
BackgroundThe Promise and Pitfalls of Big Data Studies in Perioperative Medicine
Mathis, M. R., Janda, A. M., & Kheterpal, S. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-83399-8.00005-3 · Cited by 1
Wiklund, E., Carlander, J., Wagner, P., Engdahl, M., Chabok, A., & Nikberg, M. (2023) · Journal of Robotic Surgery · doi:10.1007/s11701-023-01571-5 · Cited by 1
“Therefore, post hoc findings from the secondary analyses should be interpreted with caution, as statistical power may be lacking to detect associations with additional risk factors and there may be potential pitfalls in identifying their origin [38].”
BackgroundPepetone, A., Qutub, M., Andrade, L., Wallace, M. P., & Kirkpatrick, S. I. (2023) · Canadian Journal of Dietetic Practice and Research · doi:10.3148/cjdpr-2023-003 · Cited by 1
Haenssgen, M. J., Charoenboon, N., Early, A., & Althaus, T. (2023) · Tropical Medicine & International Health · doi:10.1111/tmi.13926 · Cited by 1
“…contexts (which remains subject to future research), the potential conflation of exposure and confounder variables means that statistical associations between potential behavioural drivers and fever treatment process characteristics should be considered indicative rather than definitive [ 53].”
Major‐Smith, D., Morgan, J., Halstead, I. N., Tohidinik, H. R., Iles‐Caven, Y., Golding, J., & Northstone, K. (2023) · Wellcome Open Research · doi:10.12688/wellcomeopenres.17897.3 · Cited by 1
“For example, say that we are interested in whether RSBB impacts mental health, and we are deciding whether to include marital status as a confounder or not 5,7,40 .”
Does China’s aid increase individual happiness of recipient countries?
Xu, J., & Sun, C. (2023) · Empirical Economics · doi:10.1007/s00181-023-02537-0 · Cited by 1
Foti, K. E., Coresh, J., Whelton, P. K., Matsushita, K., Hardy, S. T., Reynolds, K., Bowling, C. B., Walker, K. A., Kucharska‐Newton, A., Windham, B. G., et al. (2024) · Hypertension · doi:10.1161/hypertensionaha.123.21823 · Cited by 1
“39 Additionally, changes in participant characteristics between visits 1 and 5 may not capture potentially clinically relevant fluctuations in these characteristics that may have occurred between time points.”
BackgroundUzar, H., Karadoğan, E., & Cakir, B. (2024) · Uludağ Üniversitesi Tıp Fakültesi Dergisi · doi:10.32708/uutfd.1463926 · Cited by 1
Housing conditions and risk of incident COPD: a Danish cohort study, 2000–2018
Kloster, S., Kirkegaard, A. M., Davidsen, M., Christensen, A. I., Nielsen, N. S., Gunnarsen, L., Vestbo, J., & Ersbøll, A. K. (2024) · BMC Public Health · doi:10.1186/s12889-024-19131-3 · Cited by 1
“A further strength of the study is that we included a unique set of confounders for each studied exposure, thereby minimizing the risk of confounding or, e.g., controlling for a mediator (a concept known as Table 2 Fallacy [38, 39]).”
BackgroundUgheoke, S. O. (2024) · Malaysian Management Journal · doi:10.32890/mmj2024.28.9 · Cited by 1
Lim, Z. J., Karalapillai, D., Kolawole, H., Fiddes, C., Pilcher, D., & Subramaniam, A. (2024) · Critical Care and Resuscitation · doi:10.1016/j.ccrj.2024.06.002 · Cited by 1
Regression Methods for Epidemiological Analysis
Greenland, S. (2024) · Springer eBooks · doi:10.1007/978-1-4614-6625-3_17-2 · Cited by 2
Self-citationNatural Course and Predictors of Sustained Exergaming in Young Adults
O’Loughlin, E. K., Sabiston, C. M., Riglea, T., Naja, M., Bélanger, M. F., Wellman, R. J., Sylvestre, M., & O’Loughlin, J. L. (2024) · Games for Health Journal · doi:10.1089/g4h.2024.0021 · Cited by 1
“27,28 We concluded that a variable was associated with sustained exergaming if the CI for the estimate excluded the null value of 1.0.”
InfluentialChauvet‐Gélinier, J., Cottenet, J., Jollant, F., & Quantin, C. (2024) · Epidemiology and Psychiatric Sciences · doi:10.1017/s2045796024000568 · Cited by 1
“For this analysis, we presented the effect of all adjustment variables, but it should be noted that only the effect of SARS-CoV-2 infection is considered as the total effect on the risk of readmission for self-harm (Westreich 2013).”
Gustavsen, E. M., Norderval, S., Dørum, L. M., Balto, A., Heimdal, R., Vonen, B., Stensland, E., Haukland, E. C., & Hauglann, B. (2024) · Research in Health Services & Regions · doi:10.1007/s43999-024-00057-7 · Cited by 1
“Directed acyclic graphs (DAGs) were used in separate analyses to avoid Table 2 fallacy [31].”
Hernandez, C. J., Trujillo, D., Tate, M., Baguso, G. N., Quintana, J., McNaughten, K. C., Jain, J. P., Santos, G., Arayasirikul, S., McFarland, W., et al. (2025) · AIDS and Behavior · doi:10.1007/s10461-024-04608-4 · Cited by 1
“…the impacts of multiple factors are derived from a single multivariable model especially when there is more than one exposure of interest, we built a multivariable Poisson regression with a robust error variance model for each exposure while controlling for age, race/ethnicity and HIV status [36].”
Sociodemographic inequities in overall survival among younger and older women with cervical cancer
Holt, H. K., Calip, G. S., Peterson, C. E., MacLaughlan, S. D., GELLER, S. E., & Guadamuz, J. S. (2025) · Cancer Causes & Control · doi:10.1007/s10552-025-01961-0 · Cited by 1
“We did not present fully adjusted models for all these sociodemographic factors in one model as they are each likely on the causal pathway and thus interrelated [31].”
Cowan, L. M., Adamestam, I., Masterson, J. A., Beatty, M., Boardman, J. P., Chislett, L., Johnston, P., Joss, J., Lawrence, H., Litchfield, K., et al. (2025) · Journal of the Intensive Care Society · doi:10.1177/17511437251313700 · Cited by 1
Abdelaziz, A., Sarker, J., Lien, P.-W., Williams, D. J., Grijalva, C. G., Lee, T. A., & Antoon, J. W. (2025) · The Journal of Pediatrics · doi:10.1016/j.jpeds.2025.114574 · Cited by 1
Mikl, J., Yu, T., Singh, S., Zhao, X., Wang, S., Devlin, A., Anton, R. F., & Pascale, V. (2025) · Journal of Studies on Alcohol and Drugs · doi:10.15288/jsad.24-00354 · Cited by 1
Factors associated with antidepressant use following hospitalization for acute stroke
Nanavati, H. D., Wright, N. C., Smith, M. J., Hardy, S. T., Howard, V. J., & Lin, C. (2025) · The International Journal of Psychiatry in Medicine · doi:10.1177/00912174251348329 · Cited by 1
A Multidimensional Model of Social Autistic Function and Its Effects on Quality of Life
Pieslinger, J., Igelström, E., & Igelström, K. M. (2025) · Autism in Adulthood · doi:10.1089/aut.2024.0262 · Cited by 1
Watson, E. J., Glass, D. J., & Petito, L. C. (2025) · American Journal of Human Biology · doi:10.1002/ajhb.70149 · Cited by 3
“The widespread naïve interpretation of covariate coefficients has been termed the “Table 2 Fallacy” (Westreich et al. 2021; Westreich and Greenland 2013).”
Oral Health and Risk of Incident Diabetes: Evidence from a Population-Based Cohort Study
Cole, M. S., Alvarez, C. M., & Farouk, A. S. (2025) · Journal of Current Research in Oral Surgery · doi:10.51847/sdbdtyjqwg · Cited by 1
Changing predictors of statin initiation in US women over two decades
Kinsey, T. L., Stürmer, T., Poole, C., Rothman, K. J., & Glynn, R. J. (2018) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.4704 · Cited by 1
Li, H., Geng, Z., Sun, X., Yu, Y., & Xue, F. (2020) · BMC Genetics · doi:10.1186/s12863-020-00876-w · Cited by 1
Tobacco, Alcohol, Drug Use, and Intimate Partner Violence Among MSM Living With HIV
(2019) · Journal of the Association of Nurses in AIDS Care · doi:10.1097/jnc.0000000000000143 · Cited by 1
Gittins, M., Carder, M., Seed, M., Iskandar, I. Y. K., Daniels, S., & van Tongeren, M. (2023) · Occupational and Environmental Medicine · doi:10.1136/oemed-2022-108627 · Cited by 1
Wei, Y., Horne, E. M. F., Knight, R., Cezard, G. I., Walker, A. J., Fisher, L., Denholm, R., Taylor, K., Walker, V. M., Riley, S., et al. (2025) · BJGP Open · doi:10.3399/bjgpo.2024.0140 · Cited by 1
Inequalities in health : social, biological, ethnic and life-course perspectives
Khanolkar, A. R. (2013) · Figshare · Cited by 1
Rankin, D. A., Rebeiro, P. F., Haddadin, Z., Halasa, N., & Greevy, R. A. (2020) · Infection Control and Hospital Epidemiology · doi:10.1017/ice.2020.123 · Cited by 1
A scoping review of causal methods enabling predictions under hypothetical interventionsPreprint
Lijing Lin, A., Sperrin, M., Jenkins, D. A., Martin, G. P., & Peek, N. B. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2011.09815 · Cited by 1
“Moreover, each clinical intervention scenario will require its own model for identifying treatment effects from observational data (11).”
BackgroundInfluentialCOVID-19 and the Epistemology of Epidemiological Models at the Dawn of AIPreprint
Ellison, G. T. H. (2020) · Preprints.org · doi:10.20944/preprints202008.0245.v1 · Cited by 1
“Nevertheless, they are commonly used as if they can and thereby invoke a form of inferential bias known as the “Table 2 fallacy” 5 (Westreich and Greenland 2013) which can lead to fundamental misinterpretation of the causal relationships involved, with potentially dangerous implications for the…”
BackgroundPieper, L. (2021) · UA Campus Repository (The University of Arizona) · Cited by 1
To Explain or to Predict: Important Aspect to Consider Also in Orthopaedics: Letter to the Editor
Reito, A. R., & Ponkilainen, V. (2021) · The American Journal of Sports Medicine · doi:10.1177/03635465211030215 · Cited by 1
Kronfli, N., Dussault, C., Maheu‐Giroux, M., Halavrezos, A., Chalifoux, S., Sherman, J. P., Park, H., Balso, L. D., Cheng, M. P., Poulin, S., et al. (2021) · SSRN Electronic Journal · doi:10.2139/ssrn.3959665 · Cited by 1
Metadata
- Authors
- Westreich, D., & Greenland, S.
- Affiliations
- Duke University (US)
- Corresponding author
- Westreich, D.
- Venue
- American Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 2013-01-30
- Volume
- 177
- Issue
- 4
- Pages
- 292-298
- ISSN
- 0002-9262 (ISSN-L)
- 1476-6256
- PMC
- PMC3626058
- OpenAlex
- W2138008655
- Cited by
- 1,276
- References
- 30
- Citations by year
- 2026: 177 · 2025: 213 · 2024: 212 · 2023: 176 · 2022: 192 · 2021: 108 · 2020: 84 · 2019: 39 · 2018: 29 · 2017: 11 · 2016: 3 · 2015: 15 · 2014: 13 · 2013: 4
- FWCI
- 10.27
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- American Journal of Epidemiology (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (AI064518)
- Duke Global Health Institute, Duke University
- University of California, Los Angeles
- National Institute of Allergy and Infectious Diseases (P30AI064518)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R00HD063961)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- causal graphs, confounding, odds ratio, logistic regression
- MeSH terms
- HIV Seropositivity, Humans, Mathematical Computing, North Carolina, Regression Analysis, Risk Factors, Smoking, Statistics as Topic, Violence, Work, HIV Infections, Confounding Factors, Epidemiologic, Multivariate Analysis, Logistic Models, Odds Ratio, Epidemiologic Studies, Risk Assessment, Stroke
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
