ArticleCurrent protocols2021
Testing Graphical Causal Models Using the R Package "dagitty".
Article in Current protocols, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 26 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed.
- Trial
- Body weight and waist circumference are differentially associated with the response to L-thyroxine treatment in primary hypothyroidism.Journal of clinical & translational endocrinology · 2026Article
- Tree growth after a major hurricane reflects predisturbance vigor rather than canopy damage.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Risk assessment for canine periodontal disease using a hybrid causal Bayesian network.Frontiers in veterinary science · 2026Article
- Nutrient connectivity via seabirds enhances dynamic measures of coral reef ecosystem function.PLoS biology · 2025Article
- How Information Exposure Shapes Risk Perceptions and Vaccination Intentions Among Gay, Bisexual, and Other Men Who Have Sex With Men: Cross-Sectional Survey Study.JMIR public health and surveillance · 2025Article
- Mechanisms of cultural diversity in urban populations.Nature communications · 2025Article
- A good move for health?: Analyzing urban exposure trajectories of residential relocation and mental health in populations in Bradford.Environmental epidemiology (Philadelphia, Pa.) · 2025Article
- Effects of intimate partner violence and homophobic bullying on ART adherence among young Thai men who have sex with men: a causal mediation analysis.BMC public health · 2025Article
- Anatomical and behavioural correlates of auditory perception in developmental dyslexia.Brain : a journal of neurology · 2025Article
- Examining Predictors of Environmental Health Knowledge and Competences in a Sample of Catalan Paediatricians.Health science reports · 2025Article
- Article
- Occurrence of COVID-19 and serumGlobal epidemiology · 2024Article
- Effects of Mobile Stroke Unit dispatch on blood pressure management and outcomes in patients with intracerebral haematoma: Results from the Berlin_Prehospital Or Usual Care Delivery in acute Stroke (B_PROUD) controlled intervention study.European stroke journal · 2024Article
- Article
- Assessing the transportability of clinical prediction models for cognitive impairment using causal models.BMC medical research methodology · 2023Article
- Article
- Emotional and informational social support from health visitors and breastfeeding outcomes in the UK.International breastfeeding journal · 2023Article
- Estimating the effect of COVID-19 on trial design characteristics: a registered report.Royal Society open science · 2023Article
- The impact of market integration on arranged marriages in Matlab, Bangladesh.Evolutionary human sciences · 2023Article
Corrections and comments
- Erratum issued
- Erratum issued
Authors and funding
3 authors.
Funding
Abstract
Causal diagrams such as directed acyclic graphs (DAGs) are used in several scientific fields to help design and analyze studies that aim to infer causal effects from observational data; for example, DAGs can help identify suitable strategies to reduce confounding bias. However, DAGs can be difficult to design, and the validity of any DAG-derived strategy hinges on the validity of the postulated DAG itself. Researchers should therefore check whether the assumptions encoded in the DAG are consistent with the data before proceeding with the analysis. Here, we explain how the R package 'dagitty', based on the web tool dagitty.net, can be used to test the statistical implications of the assumptions encoded in a given DAG. We hope that this will help researchers discover model specification errors, avoid erroneous conclusions, and build better models. © 2021 The Authors. Basic Protocol 1: Constructing and importing DAG models from the dagitty web interface Support Protocol 1: Installing R, RStudio, and the dagitty package Basic Protocol 2: Testing DAGs against categorical data Basic Protocol 3: Testing DAGs against continuous data Support Protocol 2: Testing DAGs against continuous data with non-linearities Basic Protocol 4: Testing DAGs against a combination of categorical and continuous data.
Indexed as
Identifiers
33592130What OpenQuestion holds
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.