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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Hiwar, W., King, M., Shuweihdi, F., Fletcher, L. A., Dancer, S. J., & Noakes, C. J. (2021) · Indoor Air · doi:10.1111/ina.12846 · Cited by 77
A causal roadmap for generating high-quality real-world evidence
Dang, L. E., Gruber, S., Lee, H., Dahabreh, I. J., Stuart, E. A., Williamson, B. D., Wyss, R., Diaz, I. M., Ghosh, D., Kıcıman, E., et al. (2023) · Journal of Clinical and Translational Science · doi:10.1017/cts.2023.635 · Cited by 85
“Software programs can also facilitate this process [71,72].”
Background
Associations of exposure to perfluoroalkyl substances individually and in mixtures with persistent infections: Recent findings from NHANES 1999–2016
Bulka, C. M., Avula, V. R., & Fry, R. C. (2021) · Environmental Pollution · doi:10.1016/j.envpol.2021.116619 · Cited by 70
Early-life associations between per- and polyfluoroalkyl substances and serum lipids in a longitudinal birth cohort
Blomberg, A. J., Shih, Y.-H., Messerlian, C., Jørgensen, L. H., Weihe, P., & Grandjean, P. (2021) · Environmental Research · doi:10.1016/j.envres.2021.111400 · Cited by 73
Identifying Vulnerable Periods of Neurotoxicity to Triclosan Exposure in Children
Jackson-Browne, M. S., Papandonatos, G. D., Chen, A., Calafat, A. M., Yolton, K. A., Lanphear, B. P., & Braun, J. M. (2018) · Environmental Health Perspectives · doi:10.1289/ehp2777 · Cited by 76
“In regression models, we adjusted for variables that may be associated with both triclosan exposure and child cognitive abilities based on the results of previous studies and a directed acyclic graph (see Figure S1; Textor et al. 2016) (Bellinger 2004; Stacy et al.”
Method
Prevalence of Diabetes and Hypertension and Their Associated Risks for Poor Outcomes in Covid-19 Patients
Barrera, F. J., Shekhar, S., Wurth, R., Moreno-Peña, P. J., Ponce, O. J., Hajdenberg, M., Álvarez‐Villalobos, N. A., Hall, J. E., Schiffrin, E. L., Eisenhofer, G., et al. (2020) · Journal of the Endocrine Society · doi:10.1210/jendso/bvaa102 · Cited by 71
“To identify confounders, we designed a directed acyclic graph (DAG) in R [27, 37-41].”
Method
Prevalence and Factors Associated with Falls among Older Outpatients
Ha, V.-A. T., Nguyen, T. N., Nguyen, T. X., Nguyen, H. T. T., Nguyen, T. T. H., Nguyen, A. T., Pham, T., & Vu, H. T. T. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18084041 · Cited by 70
“DAGs were used to construct the conceptual diagram representing causal relationships of all variables in the network [27,28].”
Method
Local fit evaluation of structural equation models using graphical criteria.
Thoemmes, F. J., Rosseel, Y., & Textor, J. C. (2017) · Psychological Methods · doi:10.1037/met0000147 · Cited by 82
“This code includes the data-generating models, all standard output of the SEM software lavaan (Rosseel, 2012), and the local tests provided by the R package dagitty (Textor et al., 2016).”
MethodSelf-citation
Low and High Ambient Temperatures during Pregnancy and Birth Weight among 624,940 Singleton Term Births in Israel (2010–2014): An Investigation of Potential Windows of Susceptibility
Basagaña, X., Michael, Y., Lensky, I. M., Rubin, L., Grotto, I., Vadislavsky, E., Levi, Y., Amitai, E., & Agay‐Shay, K. (2021) · Environmental Health Perspectives · doi:10.1289/ehp8117 · Cited by 69
“Covariates included in adjusted models were selected based on prior knowledge and directed acyclic graphs (DAGs) (Greenland et al. 1999; Textor et al. 2016) (Figure S4).”
Association Between Exposure to Outdoor Artificial Light at Night and Sleep Disorders Among Children in China
Wang, L.-B., Gong, Y.-C., Fang, Q.-L., Cui, X.-X., Dharmage, S. C., Jalaludin, B. B., Knibbs, L. D., Bloom, M. S., Guo, Y., Lin, L., et al. (2022) · JAMA Network Open · doi:10.1001/jamanetworkopen.2022.13247 · Cited by 69
Chimpanzee pant‐hoots encode individual information more reliably than group differences
Desai, N. P., Fedurek, P., Slocombe, K. E., & Wilson, M. L. (2022) · American Journal of Primatology · doi:10.1002/ajp.23430 · Cited by 66
“The adjustmentSets function in the R ‐ package dagitty prints a list of all minimally sufficient adjustment sets (Textor et al., 2016).”
Background
Association between Excessive Daytime Sleepiness and Risk of Cardiovascular Disease and All-Cause Mortality: A Systematic Review and Meta-Analysis of Longitudinal Cohort Studies
Wang, L., Liu, Q., Heizhati, M., Yao, X., Luo, Q., & Li, N. (2020) · Journal of the American Medical Directors Association · doi:10.1016/j.jamda.2020.05.023 · Cited by 70
Impact of exposure time in awake prone positioning on clinical outcomes of patients with COVID-19-related acute respiratory failure treated with high-flow nasal oxygen: a multicenter cohort study
Esperatti, M., Busico, M., Fuentes, N. A., Gallardo, A., Osatnik, J., Vitali, A., Wasinger, E. G., Olmos, M., Quintana, J., Saavedra, S. N., et al. (2022) · Critical Care · doi:10.1186/s13054-021-03881-2 · Cited by 65
“Based on subject matter knowledge and previous literature, we used a direct acyclic graph (DAG) to identify and select variables potentially associated with both awake prone positioning and study outcomes [21, 22] (Additional File 1: Fig.”
Method
Race, the Vaginal Microbiome, and Spontaneous Preterm Birth
Sun, S., Serrano, M. G., Fettweis, J. M., Basta, P. V., Rosen, E. M., Ludwig, K., Sorgen, A. A., Blakley, I., Wu, M. C., Dole, N., et al. (2022) · mSystems · doi:10.1128/msystems.00017-22 · Cited by 67
“For the purpose of multivariable adjusted analyses, we identified a minimally sufficient subset of adjustment variables based on a directed acyclic graph (DAG) (48) using daggity (49).”
Method
Association of urinary bisphenols during pregnancy with maternal, cord blood and childhood thyroid function
Derakhshan, A., Philips, E. M., Ghassabian, A., Santos, S., Asimakopoulos, A. G., Kannan, K., Kortenkamp, A., Jaddoe, V. W. V., Trasande, L., Peeters, R. P., et al. (2020) · Environment International · doi:10.1016/j.envint.2020.106160 · Cited by 63
Residential surrounding greenness and self-reported symptoms of anxiety and depression in adolescents
Hartley, K., Perazzo, J. D., Brokamp, C., Gillespie, G. L., Cecil, K. M., LeMasters, G. K., Yolton, K. A., & Ryan, P. (2020) · Environmental Research · doi:10.1016/j.envres.2020.110628 · Cited by 66
Financial Hardship and Quality of Life among African American and White Cancer Survivors: The Role of Limiting Care Due to Cost
Hastert, T. A., Kyko, J. M., Reed, A. R., Harper, F. W. K., Beebe‐Dimmer, J., Baird, T. E., & Schwartz, A. G. (2019) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-18-1336 · Cited by 63
“Additional covariates were selected using a directed acyclic graph (DAG) including relationships between financial hardship, limiting care, HRQOL, and each of the factors listed in Table 1 (31).”
Method
Associations Between Race/Ethnicity and US Childhood and Adolescent Cancer Survival by Treatment Amenability
Delavar, A., Barnes, J. M., Wang, X., & Johnson, K. J. (2020) · Archives of Pediatrics and Adolescent Medicine · doi:10.1001/jamapediatrics.2019.6074 · Cited by 63
Inorganic arsenic exposure and neuropsychological development of children of 4–5 years of age living in Spain
Signes‐Pastor, A. J., Vioqué, J., Navarrete‐Muñoz, E. M., Carey, M. P., García‐Villarino, M., Fernández‐Somoano, A., Tardón, A., Santa‐Marina, L., Irizar, A., Casas, M., et al. (2019) · Environmental Research · doi:10.1016/j.envres.2019.04.028 · Cited by 62
Community-level signatures of ecological succession in natural bacterial communities
Pascual‐García, A., & Bell, T. (2020) · Nature Communications · doi:10.1038/s41467-020-16011-3 · Cited by 62
Neighbourhood fast food exposure and consumption: the mediating role of neighbourhood social norms
van Rongen, S., Poelman, M. P., Thornton, L. E., Abbott, G., Lü, M., Kamphuis, C. B. M., Verkooijen, K. T., & de Vet, E. (2020) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-020-00969-w · Cited by 65
Outdoor Play as a Mitigating Factor in the Association Between Screen Time for Young Children and Neurodevelopmental Outcomes
Sugiyama, M., Tsuchiya, K. J., Okubo, Y., Rahman, M. S., Uchiyama, S., Harada, T., Iwabuchi, T., Okumura, A., Nakayasu, C., Amma, Y., et al. (2023) · Archives of Pediatrics and Adolescent Medicine · doi:10.1001/jamapediatrics.2022.5356 · Cited by 79
Organophosphate pesticide metabolite concentrations in urine during pregnancy and offspring attention-deficit hyperactivity disorder and autistic traits
van den Dries, M. A., Guxens, M., Pronk, A., Spaan, S., Marroun, H. E., Jusko, T. A., Longnecker, M. P., Ferguson, K. K., & Tiemeier, H. W. (2019) · Environment International · doi:10.1016/j.envint.2019.105002 · Cited by 65
Phthalate and Bisphenol Exposure during Pregnancy and Offspring Nonverbal IQ
van den Dries, M. A., Guxens, M., Spaan, S., Ferguson, K. K., Philips, E. M., Santos, S., Jaddoe, V. W. V., Ghassabian, A., Trasande, L., Tiemeier, H. W., et al. (2020) · Environmental Health Perspectives · doi:10.1289/ehp6047 · Cited by 61
“These potential confounders were selected a priori de ﬁ ned with a directed acyclic graph (DAG) (Textor et al. 2016) based on previous studies of prenatal phthalate and bisphenol exposure and child neurodevelopment and on biologically plausible covariate – exposure and covariate – outcome associations observed in our…”
Food consumption by degree of food processing and risk of type 2 diabetes mellitus: a prospective cohort analysis of the European Prospective Investigation into Cancer and Nutrition (EPIC)
Dicken, S. J., Dahm, C. C., Ibsen, D. B., Olsen, A., Tjønneland, A. M., Hajji-Louati, M., Cadeau, C., Marques, C., Schulze, M. B., Jannasch, F., et al. (2024) · The Lancet Regional Health - Europe · doi:10.1016/j.lanepe.2024.101043 · Cited by 66
“Total effects (TE) (the sum of the PNDE and TNIE) were then decomposed into the direct and indirect effect to estimate the proportion mediated (PM) (the ratio of TNIE to TE).”
Early Childhood Antibiotic Treatment for Otitis Media and Other Respiratory Tract Infections Is Associated With Risk of Type 1 Diabetes: A Nationwide Register-Based Study With Sibling Analysis
Wernroth, M.-L., Fall, K., Svennblad, B., Ludvigsson, J. F., Sjölander, A., Almqvist, C., & Fall, T. (2020) · Diabetes Care · doi:10.2337/dc19-1162 · Cited by 57
“model for estimating the total effect of antibiotics on type 1 diabetes (22).”
Background
Causal Diagram Techniques for Urologic Oncology Research
Shapiro, D. D., & Msaouel, P. (2020) · Clinical Genitourinary Cancer · doi:10.1016/j.clgc.2020.08.003 · Cited by 59
All coffee types decrease the risk of adverse clinical outcomes in chronic liver disease: a UK Biobank study
Kennedy, O. J., Fallowfield, J. A., Poole, R., Hayes, P. C., Parkes, J., & Roderick, P. J. (2021) · BMC Public Health · doi:10.1186/s12889-021-10991-7 · Cited by 58
First‐Trimester Maternal Folic Acid Supplementation Reduced Risks of Severe and Most Congenital Heart Diseases in Offspring: A Large Case‐Control Study
Qu, Y., Lin, S., Zhuang, J., Bloom, M. S., Smith, M., Nie, Z., Mai, J., Ou, Y., Wu, Y., Gao, X., et al. (2020) · Journal of the American Heart Association · doi:10.1161/jaha.119.015652 · Cited by 58
Adherence to the EAT-Lancet diet is associated with a lower risk of type 2 diabetes: the Danish Diet, Cancer and Health cohort
Langmann, F., Ibsen, D. B., Tjønneland, A. M., Olsen, A., Overvad, K., & Dahm, C. C. (2023) · European Journal of Nutrition · doi:10.1007/s00394-023-03090-3 · Cited by 59
“Covariates were selected a priori based on a review of the literature and directed acyclic graphs [30, 31] (Online Resource Supplementary Fig.”
Method
Surgical site infection after hip fracture – mortality and risk factors: an observational cohort study of 1,709 patients
Pollmann, C. T., Dahl, F. A., Røtterud, J. H., Gjertsen, J., & Årøen, A. (2020) · Acta Orthopaedica · doi:10.1080/17453674.2020.1717841 · Cited by 58
“In all multivariable models, the variables to be adjusted for were chosen from directed acyclic graphs (DAG), which were constructed using DAGitty (Textor et al. 2017).”
Method
Impact of ADAR-induced editing of minor viral RNA populations on replication and transmission of SARS-CoV-2
Ringlander, J., Fingal, J., Kann, H., Prakash, K., Rydell, G. E., Andersson, M., Martner, A., Lindh, M., Horal, P., Hellstrand, K., et al. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2112663119 · Cited by 57
Theory and performance of substitution models for estimating relative causal effects in nutritional epidemiology
Tomova, G. D., Gilthorpe, M. S., & Tennant, P. W. G. (2022) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/nqac188 · Cited by 57
“3-1 (22) based on a prespecified data generation process depicted in Figure 1.”
BackgroundSelf-citation
Factors associated with lift equipment use during patient lifts and transfers by hospital nurses and nursing care assistants: A prospective observational cohort study
Kucera, K. L., Schoenfisch, A. L., McIlvaine, J., Becherer, L., James, T. M., Yeung, Y.-L., Avent, S., & Lipscomb, H. J. (2018) · International Journal of Nursing Studies · doi:10.1016/j.ijnurstu.2018.11.006 · Cited by 56
Associations between online pornography consumption and sexual dysfunction in young men: multivariate analysis based on an international web-based survey
Jacobs, T., Geysemans, B., Van Hal, G., Glazemakers, I., Fog-Poulsen, K., Vermandel, A., De Wachter, S., & De Win, G. (2021) · JMIR Public Health and Surveillance · doi:10.2196/32542 · Cited by 55
“0 web application and included in a multivariable regression analysis [45].”
Impact of CD19 CAR T-cell product type on outcomes in relapsed or refractory aggressive B-NHL
Gauthier, J., Gazeau, N., Hirayama, A. V. V., Hill, J. A., Wu, V., Cearley, A., Perkins, P., Kirk, A., Shadman, M. S., Chow, V. A., et al. (2022) · Blood · doi:10.1182/blood.2021014497 · Cited by 57
Emergence and Causality in Complex Systems: A Survey of Causal Emergence and Related Quantitative Studies
Yuan, B., Zhang, J., Lyu, A., Wu, J., Wang, Z., Yang, M., Liu, K., Mou, M., & Cui, P. (2024) · Entropy · doi:10.3390/e26020108 · Cited by 70
The Role of Causality in Explainable Artificial Intelligence
Carloni, G., Berti, A., & Colantonio, S. (2025) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.70015 · Cited by 99
Association of novel measures of sleep disturbances with blood pressure: the Multi-Ethnic Study of Atherosclerosis
Kim, J. S., Azarbarzin, A., Wang, R., Djonlagic, I. E., Punjabi, N. M., Zee, P. C., Koo, B. B., Soliman, E. Z., Younes, M. K., & Redline, S. S. (2019) · Thorax · doi:10.1136/thoraxjnl-2019-213533 · Cited by 55
Prenatal exposure to organophosphate pesticides and brain morphology and white matter microstructure in preadolescents
van den Dries, M. A., Lamballais, S., Marroun, H. E., Pronk, A., Spaan, S., Ferguson, K. K., Longnecker, M. P., Tiemeier, H. W., & Guxens, M. (2020) · Environmental Research · doi:10.1016/j.envres.2020.110047 · Cited by 57
Association of per- and polyfluoroalkyl substances with thyroid homeostasis during pregnancy in the SELMA study
Derakhshan, A., Kortenkamp, A., Shu, H., Broeren, M. A. C., Lindh, C. H., Peeters, R. P., Bornehag, C., DEMENEIX, B. A., & Korevaar, T. I. M. (2022) · Environment International · doi:10.1016/j.envint.2022.107420 · Cited by 53
Prenatal Ambient Ultrafine Particle Exposure and Childhood Asthma in the Northeastern United States
Wright, R. J., Hsu, H.-H. L., Chiu, Y.-H. M., Coull, B. A., Simon, M. C., Hudda, N., Schwartz, J., Kloog, I., & Durant, J. L. (2021) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.202010-3743oc · Cited by 53
Community design and hypertension: Walkability and park access relationships with cardiovascular health
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Validation of the days alive and out of hospital outcome measure after emergency laparotomy: a retrospective cohort study
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Global Plasma Metabolomics to Identify Potential Biomarkers of Blood Pressure Progression
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“Mass gathering events and COVID-19 transmission in Borriana (Spain): A retrospective cohort study”
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“0) [44], together with inverse probability weighted regression [45] to obtain adjusted AR (aAR) and RR (aRR).”

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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