ArticleInternational journal of epidemiology2019
DAG-informed regression modelling, agent-based modelling and microsimulation modelling: a critical comparison of methods for causal inference.
Article in International journal of epidemiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
29 citing papers in PubMed, 1 synthesis or guideline pooled it, 54 citations in OpenAlex.
- Applications of causal and structural equation modeling in epidemiology: a systematic and critical review.BMC medical research methodology · 2026Pooled it
- Article
- Exploring spillover effects beyond workplace dietary interventions using agent-based modelling.Public health nutrition · 2026Article
- A spatially dynamic agent-based model for assessing the effect of gentrification-induced migration and HIV transmission among heterosexual African American/Black women.Annals of epidemiology · 2025Article
- Assessing differences in country-level estimates of maternal mortality: a comparison of GMatH, UN, and GBD model results for 2020.EClinicalMedicine · 2025Article
- Composite variable bias: causal analysis of weight outcomes.International journal of obesity (2005) · 2025Article
- Clusters and associations of adverse neonatal events with adult risk of multimorbidity: A secondary analysis of birth cohort data.PloS one · 2025Article
- Impact of Noradrenaline Administration Dosage on the Occurrence of Peripheral Intravenous Catheter-Related Venous Phlebitis in Critically Ill Patients Using a Time-Dependent Multilevel Cox Regression Model.Emergency medicine international · 2025Article
- Short-term impacts of Universal Basic Income on population mental health inequalities in the UK: A microsimulation modelling study.PLoS medicine · 2024Article
- Incarceration's lingering health effects on Black men: impacts persist into retirement.AIMS public health · 2024Article
- Applications of agent-based modeling in trauma research.Psychological trauma : theory, research, practice and policy · 2023Article
- Simulation-based estimates and projections of global, regional and country-level maternal mortality by cause, 1990-2050.Nature medicine · 2023Article
- A simulation-based comparative effectiveness analysis of policies to improve global maternal health outcomes.Nature medicine · 2023Article
- Effects of poverty on mental health in the UK working-age population: causal analyses of the UK Household Longitudinal Study.International journal of epidemiology · 2023Article
- Effect of biological, psychological, and social factors on maternal depressive symptoms in late pregnancy: a cross-sectional study.Frontiers in psychiatry · 2023Article
- Applications of Complex Systems Models to Improve Retail Food Environments for Population Health: A Scoping Review.Advances in nutrition (Bethesda, Md.) · 2022Article
- A Mediterranean diet microsimulation modeling in relation to cardiovascular disease burden: the ATTICA and GREECS epidemiological studies.European journal of clinical nutrition · 2022Article
- G-Computation and Agent-Based Modeling for Social Epidemiology: Can Population Interventions Prevent Posttraumatic Stress Disorder?American journal of epidemiology · 2022Article
- Causal evidence in health decision making: methodological approaches of causal inference and health decision science.German medical science : GMS e-journal · 2022Review
- Assessing causality in epidemiology: revisiting Bradford Hill to incorporate developments in causal thinking.European journal of epidemiology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The current paradigm for causal inference in epidemiology relies primarily on the evaluation of counterfactual contrasts via statistical regression models informed by graphical causal models (often in the form of directed acyclic graphs, or DAGs) and their underlying mathematical theory. However, there have been growing calls for supplementary methods, and one such method that has been proposed is agent-based modelling due to its potential for simulating counterfactuals. However, within the epidemiological literature, there currently exists a general lack of clarity regarding what exactly agent-based modelling is (and is not) and, importantly, how it differs from microsimulation modelling-perhaps its closest methodological comparator. We clarify this distinction by briefly reviewing the history of each method, which provides a context for their similarities and differences, and casts light on the types of research questions that they have evolved (and thus are well suited) to answering; we do the same for DAG-informed regression methods. The distinct historical evolutions of DAG-informed regression modelling, microsimulation modelling and agent-based modelling have given rise to distinct features of the methods themselves, and provide a foundation for critical comparison. Not only are the three methods well suited to addressing different types of causal questions, but, in doing so, they place differing levels of emphasis on fixed and random effects, and also tend to operate on different timescales and in different timeframes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.