Cited by 2,295Advanced Causal Inference TechniquesBayesian Modeling and Causal InferenceStatistical Methods in Epidemiology

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Robust causal inference using directed acyclic graphs: the R package ‘dagitty’

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Textor, Johannes, van der Zander, Benito, Gilthorpe, Mark S., Liśkiewicz, Maciej, Ellison, George T.H.·2017·International Journal of Epidemiology

DOI 10.1093/ije/dyw341

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Abstract

Directed acyclic graphs (DAGs), which offer systematic representations of causal relationships, have become an established framework for the analysis of causal inference in epidemiology, often being used to determine covariate adjustment sets for minimizing confounding bias. DAGitty is a popular web application for drawing and analysing DAGs. Here we introduce the R package 'dagitty', which provides access to all of the capabilities of the DAGitty web application within the R platform for statistical computing, and also offers several new functions. We describe how the R package 'dagitty' can be used to: evaluate whether a DAG is consistent with the dataset it is intended to represent; enumerate 'statistically equivalent' but causally different DAGs; and identify exposure-outcome adjustment sets that are valid for causally different but statistically equivalent DAGs. This functionality enables epidemiologists to detect causal misspecifications in DAGs and make robust inferences that remain valid for a range of different DAGs. The R package 'dagitty' is available through the comprehensive R archive network (CRAN) at [https://cran.r-project.org/web/packages/dagitty/]. The source code is available on github at [https://github.com/jtextor/dagitty]. The web application 'DAGitty' is free software, licensed under the GNU general public licence (GPL) version 2 and is available at [http://dagitty.net/].

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Mcdougal, L., Singh, A., Kumar, K., Dehingia, N., Barros, A., Ewerling, F., Atmavilas, Y., & Raj, A. (2021) · PLoS ONE · doi:10.1371/journal.pone.0248391 · Cited by 20
“confounding (generally termed a minimal sufficient adjustment set) [69,70,82].”
BackgroundMethod
Interpregnancy weight gain and childhood obesity: analysis of a UK population-based cohort
Ziauddeen, N., Huang, J. Y., Taylor, E. J., Roderick, P. J., Godfrey, K. M., & Alwan, N. A. (2021) · International Journal of Obesity · doi:10.1038/s41366-021-00979-z · Cited by 22
“The selection of covariates into the multivariable models were guided by a directed acyclic graph (DAG) (Supplementary Figure 1) constructed using DAGitty (30) .”
Declining prevalence of cerebral palsy in children born at term in Denmark
Larsen, M. L., Rackauskaite, G., Greisen, G. O., Laursen, B., Uldall, P. V., Krebs, L., & Hoei‐Hansen, C. E. (2021) · Developmental Medicine & Child Neurology · doi:10.1111/dmcn.15136 · Cited by 22
“net, Nijmegen, the Netherlands).(15) Adjusted multivariable models are presented in Table S1 (online supporting information), choosing the minimal sufficient adjustment sets with the lowest number of missing data and/or least number of confounders.”
Background
The association of hypertension and prehypertension with greenness and PM2.5 in urban environment
Chien, J., Wu, C. W., & Chan, C. (2022) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2022.153526 · Cited by 22
Visualization of causation in social-ecological systems
Banitz, T., Hertz, T., Johansson, L., Lindkvist, E. A. L., Martínez-Peña, R., Radosavljevic, S., Schlüter, M., Wennberg, K., Ylikoski, P., & Grimm, V. (2022) · Ecology and Society · doi:10.5751/es-13030-270131 · Cited by 11
“An indirect path connects the two variables in the same direction as the direct arrow, but via a third variable, which is therefore a mediator (Textor et al. 2016, Lederer et al. 2019).”
Background
Hyperuricemia and Its Association with Osteoporosis in a Large Asian Cohort
Li, J.-Y., Lee, J., Lu, C., Su, Y.-D., Chiu, C.-T., Chen, S., Geng, J., & Chen, C. (2022) · Nutrients · doi:10.3390/nu14112206 · Cited by 22
“The directed acyclic graph was drawn using the program daggity [29,30].”
Method
Vaccine hesitancy and COVID-19 immunization among rural young adults
Mann, S., Christini, K., Chai, Y., Chang, C.-P., Hashibe, M., & Kepka, D. (2022) · Preventive Medicine Reports · doi:10.1016/j.pmedr.2022.101845 · Cited by 26
“Covariates used for model adjustments (age, gender, race and ethnicity, student status, and time of survey) were created using a Structural Causal Model, as proposed by Pearl (Pearl, 1995; Pearl, 2009; Pearl, 2009; Pearl, 2000); via a directed acyclic graph (DAG), using DAGitty (Textor et al., 2016); which visually en…”
Method
Causal Effects of Motor Control on Gait Kinematics After Orthopedic Surgery in Cerebral Palsy: A Machine-Learning Approach
Steele, K. M., & Schwartz, M. H. (2022) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2022.846205 · Cited by 22
“We identified the adjustment sets and independencies with dagitty (Textor et al., 2016) and all analyses were conducted in R (version 4.”
Method
Trimethylamine N-Oxide and Its Precursors Are Associated with Gestational Diabetes Mellitus and Pre-Eclampsia in the Boston Birth Cohort
McArthur, K., Zhang, M., Hong, X., Wang, G., Buckley, J. P., Wang, X., & Mueller, N. T. (2022) · Current Developments in Nutrition · doi:10.1093/cdn/nzac108 · Cited by 24
“Covariates were selected a priori based on a causal diagram of the hypothesized relations between these variables (Supplemental Figure 1) (44).”
Method
Subtyping emphysematous COPD by respiratory volume change distributions on CT
Shima, H., Tanabe, N., Oguma, A., Shimizu, K., Kaji, S., Terada, K., Oguma, T., Kubo, T., Suzuki, M., Makita, H., et al. (2022) · Thorax · doi:10.1136/thoraxjnl-2021-218288 · Cited by 22
Macular Layer Thickness and Effect of BMI, Body Fat, and Traditional Cardiovascular Risk Factors: The Tromsø Study
von Hanno, T., Hareide, L. L., Småbrekke, L., Morseth, B., Sneve, M., Erke, M. G., Mathiesen, E. B., & Bertelsen, G. (2022) · Investigative Ophthalmology & Visual Science · doi:10.1167/iovs.63.9.16 · Cited by 22
“19,20,40 We acknowledge that this has allowed our models to include “abundant” adjustment (i.e. included factors that do not reach statistical significant level or do not [substantially] change estimates of the effect of the factor of interest).”
Dietary fibre in relation to asthma, allergic rhinitis and sensitization from childhood up to adulthood
Sdona, E., Ekström, S., Andersson, N., Håkansson, N., Wolk, A., Westman, M., van Hage, M., Kull, I., Melén, E., & Bergström, A. (2022) · Clinical and Translational Allergy · doi:10.1002/clt2.12188 · Cited by 22
“25,26 In the multivariable model, we adjusted for sex, total energy intake (kcal/day) at 8 years, parental education (elementary school, high school, university), parental ethnicity (born in or outside of Scandinavia), parental history of atopic disease (yes/no) and maternal smoking in pregnancy…”
SEMgraph: an R package for causal network inference of high-throughput data with structural equation models
Grassi, M., Palluzzi, F., & Tarantino, B. (2022) · Bioinformatics · doi:10.1093/bioinformatics/btac567 · Cited by 26
“, 2012], dagitty [Textor et al., 2016], and GGMncv [Williams, 2020] constitute the backbone for DAG estimation and BAP search.”
Background
Association of Proton Pump Inhibitor Use With Risk of Acquiring Drug-Resistant Enterobacterales
Willems, R. P. J., Schut, M. C., Kaiser, A. M., Groot, T., Abu–Hanna, A., Twisk, J. W. R., van Dijk, K., & Vandenbroucke‐Grauls, C. M. J. E. (2023) · JAMA Network Open · doi:10.1001/jamanetworkopen.2023.0470 · Cited by 25
Association of cardiovascular risk factors and blood biomarkers with cognition: The HABS‐HD study
Jiang, X., O’Bryant, S. E., Johnson, L. A., Rissman, R. A., Yaffe, K. S., & The Health and Aging Brain Study (HABS‐HD) Study Team (2023) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1002/dad2.12394 · Cited by 21
Associations of stress and stress-related psychiatric disorders with GrimAge acceleration: review and suggestions for future work
Protsenko, E., Wolkowitz, O. M., & Yaffe, K. S. (2023) · Translational Psychiatry · doi:10.1038/s41398-023-02360-2 · Cited by 26
“While we await such studies, we hope that the framework outlined in this review will facilitate high-quality cross-sectional research built on consensus methods and with important implications for psychiatric care.”
Occupational exposure to nanomaterials and biomarkers in exhaled air and urine: Insights from the NanoExplore international cohort
Hemmendinger, M., Squillacioti, G., Charreau, T., Garzaro, G., Ghelli, F., Bono, R., Sauvain, J., Suárez, G., Hopf, N. B., Wild, P. P., et al. (2023) · Environment International · doi:10.1016/j.envint.2023.108157 · Cited by 22
Lost without a cause: time to embrace causal thinking using Directed Acyclic Graphs (DAGs)
Cauwenberg, J. V., Paepe, A. L. D., & Poppe, L. (2023) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-023-01545-8 · Cited by 22
“Finally, a very useful tool to start drawing your own DAGs is ‘dagitty’ that can be used in a browser-based environment (https://dagitty.net/) as well as with an R package [13].”
BackgroundMethod
Failure of vital sign normalization is more strongly associated than single measures with mortality and outcomes
Levin, N. M., Horton, D., Sanford, M. N., Horne, B. D., Saseendran, M., Graves, K., White, M. A., & Tonna, J. E. (2019) · The American Journal of Emergency Medicine · doi:10.1016/j.ajem.2019.12.024 · Cited by 22
Severe outcomes of COVID-19 among patients with COPD and asthma
Hansen, E., Møller, A. L., Backer, V., Andersen, M. P., Køber, L., Kragholm, K. H., & Torp-Pedersen, C. T. (2020) · ERJ Open Research · doi:10.1183/23120541.00594-2020 · Cited by 22
Severe acute malnutrition promotes bacterial binding over proinflammatory cytokine secretion by circulating innate immune cells
Phiri, T. N., Mutasa, K., Rukobo, S., Govha, M., Mushayanembwa, P., Mwakamui, S., Haider, T., Zyambo, K., Dumbura, C., Tome, J., et al. (2023) · Science Advances · doi:10.1126/sciadv.adh2284 · Cited by 21
“S9A) ( 66 ).”
Increased risk of preterm birth due to heat exposure during pregnancy: Exploring the mechanism of fetal physiology
Wang, L., Zhang, C., Di, J., Wang, Q., Ren, M., Huang, A., Chen, S., Zhao, W., Hu, H., Wang, A., et al. (2024) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2024.172730 · Cited by 21
From Prediction to Prescription: Machine Learning and Causal Inference for the Heterogeneous Treatment Effect
Abécassis, J., Dumas, É., Alberge, J., & Varoquaux, G. P. (2025) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-103123-095750 · Cited by 26
Respiratory parameters and acute kidney injury in acute respiratory distress syndrome: a causal inference study
Leite, T. T., Gomes, C. A. M., Valdivia, J. M. C., & Libório, A. B. (2019) · Annals of Translational Medicine · doi:10.21037/atm.2019.11.92 · Cited by 20
Association between dietary protein intake and changes in health-related quality of life in older adults: findings from the AusDiab 12-year prospective study
Matison, A. P., Milte, C. M., Shaw, J. E., Magliano, D. J., Daly, R. M., & Torres, S. J. (2022) · BMC Geriatrics · doi:10.1186/s12877-022-02894-y · Cited by 23
“Directed acyclic graphs [51] were used to assist with the identification of key confounders based on assumed directions of associations between covariates, the exposure and the outcome (Supplemental Fig.”
Method
Dietary patterns, breakfast consumption, meals with family and associations with common mental disorders in adolescents: a school-based cross-sectional study
Gratão, L. H. A., Pessoa, M. C., da Silva, T. P. R., Rocha, L. L., Inácio, M. L. C., de Oliveira, T. R. P. R., Cunha, C. D. F., & Mendes, L. L. (2022) · BMC Public Health · doi:10.1186/s12889-022-13367-7 · Cited by 23
Associations between diet quality and depression, anxiety, and fatigue in multiple sclerosis
Saul, A., Taylor, B. V., Blizzard, L., Simpson, S., Oddy, W. H., Probst, Y., Black, L. J., Ponsonby, A., Broadley, S., Lechner‐Scott, J., et al. (2022) · Multiple Sclerosis and Related Disorders · doi:10.1016/j.msard.2022.103910 · Cited by 21
Prenatal Perfluorooctanoic Acid (PFOA) Exposure Is Associated With Lower Infant Birthweight Within the MADRES Pregnancy Cohort
Peterson, A. K., Eckel, S. P., Habre, R., Yang, T., Faham, D., Farzan, S. F., Grubbs, B. H., Kannan, K., Robinson, M., Lerner, D. L., et al. (2022) · Frontiers in Epidemiology · doi:10.3389/fepid.2022.934715 · Cited by 23
Effect of Mobile Stroke Unit Dispatch in all Patients with Acute Stroke or TIA
Rohmann, J. L., Piccininni, M., Ebinger, M., Wendt, M., Weber, J. E., Schwabauer, E., Geisler, F., Freitag, E., Harmel, P., Lorenz‐Meyer, I., et al. (2022) · Annals of Neurology · doi:10.1002/ana.26541 · Cited by 21
Cross-sectional associations between exposure to per- and polyfluoroalkyl substances and body mass index among European teenagers in the HBM4EU aligned studies
Schillemans, T., Iszatt, N., Rémy, S., Schoeters, G. E. R., Fernández, M. F., D’Cruz, S. C., Desalegn, A. A., Haug, L. S., Lignell, S., Lindroos, A. K., et al. (2022) · Environmental Pollution · doi:10.1016/j.envpol.2022.120566 · Cited by 23
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Odo, D. B., Yang, I. A., Dey, S., Hammer, M. S., van Donkelaar, A., Martin, R. V., Dong, G., Yang, B., Hystad, P., & Knibbs, L. D. (2022) · SSRN Electronic Journal · doi:10.1016/j.envpol.2022.120916 · Cited by 23
The association of prenatal phthalates, organophosphorous pesticides, and organophosphate esters with early child language ability in Norway
Ramos, A. M., Herring, A. H., Villanger, G. D., Thomsen, C., Sakhi, A. K., Cequier, E., Aase, H., & Engel, S. M. (2023) · Environmental Research · doi:10.1016/j.envres.2023.115508 · Cited by 21
Factors associated with treatment delay and outcome in community acquired bacterial meningitis
Hovmand, N., Lundbo, L. F., Kronborg, G., Darsø, P., & Benfield, T. (2023) · IJID Regions · doi:10.1016/j.ijregi.2023.03.013 · Cited by 21
Women's negative childbirth experiences and socioeconomic factors: Results from the Babies Born better survey.
Vedeler, C., Eri, T., Nilsen, R. M., Blix, E., Downe, S., van der Wel, K. A., & Nilsen, A. B. (2023) · Sexual & Reproductive HealthCare · doi:10.1016/j.srhc.2023.100850 · Cited by 24
Extending Nontargeted Discovery of Environmental Chemical Exposures during Pregnancy and Their Association with Pregnancy Complications—A Cross-Sectional Study
Trowbridge, J., Abrahamsson, D., Bland, G. D., Jiang, T., Wang, M., Park, J.-S., Morello-Frosch, R. A., Sirota, M., Lee, H., Goin, D. E., et al. (2023) · Environmental Health Perspectives · doi:10.1289/ehp11546 · Cited by 21
Individual and joint associations of urinary phthalate metabolites with polycystic ovary and polycystic ovary syndrome: Results from the TREE cohort
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The Unfulfilled Promise of Longitudinal Designs for Causal Inference
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A novel route-based accessibility measure and its association with transit ridership
Oliveira, J. L. A., Oliveira-Neto, F. M., & Pereira, R. H. M. (2023) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2023.103916 · Cited by 21
“Based on the DAG proposed above, the minimal sufficient adjustment sets (Shrier and Platt, 2008; Textor et al., 2017) suggest there are two model specifications to estimate the total effect of accessibility on ridership removing potential biases: (i) frequency, jobs and population or (ii)…”
Leisure-Time Physical Activity and Falls With and Without Injuries Among Older Adult Women
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Sex differences in pain catastrophizing and its relation to the transition from acute pain to chronic pain
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Exploring Prenatal Exposure to Halogenated Compounds and Its Relationship with Birth Outcomes Using Nontarget Analysis
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Understanding cognitive impairment in mood disorders: mediation analyses in the UK Biobank cohort
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Prenatal Exposure to PM2.5 and Cardiac Vagal Tone during Infancy: Findings from a Multiethnic Birth Cohort
Cowell, W., Brunst, K. J., Malin, A. J., Coull, B. A., Gennings, C., Kloog, I., Lipton, L. R., Wright, R. O., Enlow, M. B., & Wright, R. J. (2019) · Environmental Health Perspectives · doi:10.1289/ehp4434 · Cited by 21

Authors: Textor, J., van der Zander, B., Gilthorpe, M. S., Liśkiewicz, M., & Ellison, G. T. H.
Affiliations: Radboud University Medical Center (NL)
University of Leeds (GB)
University of Lübeck (DE)
Corresponding author: Textor, Johannes
ORCID: Textor, Johannes
Gilthorpe, Mark S.
Liśkiewicz, Maciej
Ellison, George T.H.
Venue: International Journal of Epidemiology
Publisher: Oxford University Press (OUP)
Published: 2017-01-15
Volume: 45
Issue: 6
Pages: dyw341
ISSN: 0300-5771 (ISSN-L)
1464-3685
DOI: 10.1093/ije/dyw341
OpenAlex: W2576536258
Cited by: 2,295
References: 19
Citations by year: 2026: 156 · 2025: 409 · 2024: 451 · 2023: 392 · 2022: 323 · 2021: 256 · 2020: 201 · 2019: 74 · 2018: 22 · 2017: 6
FWCI: 35.46
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: International Journal of Epidemiology (publishedVersion)
PubMed (publishedVersion)
White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
Radboud Repository (Radboud University) (submittedVersion)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Modeling and Causal Inference
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Keywords: directed acyclic graphs, causal inference, R package, adjustment sets, confounding
MeSH terms: Data Interpretation, Statistical, Epidemiologic Methods, Humans, Software, Bias, Causality, Confounding Factors, Epidemiologic

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Robust causal inference using directed acyclic graphs: the R package ‘dagitty’

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