ArticleStatistics in medicine2020
Formulating causal questions and principled statistical answers.
Article in Statistics in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 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.
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.
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Who cites it
43 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Positive and negative parenting practices and offspring disruptive behavior: A meta-analytic review of quasi-experimental evidence.Psychological bulletin · 2025Pooled it
- Protecting Trial Integrity Through Monitoring and Analysis of Medication Adherence.Therapeutic innovation & regulatory science · 2026Review
- Choosing Covariate Balancing Methods for Causal Inference: Practical Insights From a Simulation Study.Statistics in medicine · 2026Article
- Differences in Paediatric intensive care mortality by biological sex: a study of English PICUs using linked administrative datasets.Intensive care medicine. Paediatric and neonatal · 2026Article
- Covariate selection strategies and estimands - a review of current practice of risk factor analysis from a causal perspective.BMC medical research methodology · 2025Review
- Doubly Robust Estimation of Marginal Cumulative Incidence Curves for Competing Risk Analysis.Statistics in medicine · 2025Article
- A Simple Diagnostic for the Positivity Assumption for Continuous Exposures.Statistics in medicine · 2025Article
- Causal clarity in statistical software.International journal of epidemiology · 2025Article
- Surgeon Training and Revision Rates After Patellofemoral Arthroplasty.JAMA network open · 2025Article
- Commentary: Regression Models-Efforts Are Required to Improve Statistical Practice and Teaching.Statistics in medicine · 2025Article
- Rejoinder to Commentaries on: On the Uses and Abuses of Regression Models: A Call for Reform of Statistical Practice and Teaching.Statistics in medicine · 2025Article
- Specifying a target trial protocol to estimate the effect of preconception treatment of periodontitis on time-to-pregnancy: A commentary and applied example.Community dentistry and oral epidemiology · 2025Article
- Causal Multistate Models to Evaluate Treatment Delay.Statistics in medicine · 2025Article
- Instrumental Variables Analysis and Mendelian Randomization for Causal Inference.The Journal of infectious diseases · 2025Article
- Estimating the Effect of Adhering to the Recommendations of the 2019 Canada's Food Guide on Health Outcomes in Older Adults: Protocol for a Target Trial Emulation.JMIR research protocols · 2025Article
- Tailored guidance to apply the Estimand framework to Trials within Cohorts (TwiCs) studies.Global epidemiology · 2024Article
- Risk-Based Decision Making: Estimands for Sequential Prediction Under Interventions.Biometrical journal. Biometrische Zeitschrift · 2024Article
- Propensity score weighting with survey weighted data when outcomes are binary: a simulation study.Health services & outcomes research methodology · 2024Article
- A practical guide to estimating treatment effects in patients with rheumatic diseases using real-world data.Rheumatology international · 2024Article
- Applying the estimand and target trial frameworks to external control analyses using observational data: a case study in the solid tumor setting.Frontiers in pharmacology · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Although review papers on causal inference methods are now available, there is a lack of introductory overviews on what they can render and on the guiding criteria for choosing one particular method. This tutorial gives an overview in situations where an exposure of interest is set at a chosen baseline ("point exposure") and the target outcome arises at a later time point. We first phrase relevant causal questions and make a case for being specific about the possible exposure levels involved and the populations for which the question is relevant. Using the potential outcomes framework, we describe principled definitions of causal effects and of estimation approaches classified according to whether they invoke the no unmeasured confounding assumption (including outcome regression and propensity score-based methods) or an instrumental variable with added assumptions. We mainly focus on continuous outcomes and causal average treatment effects. We discuss interpretation, challenges, and potential pitfalls and illustrate application using a "simulation learner," that mimics the effect of various breastfeeding interventions on a child's later development. This involves a typical simulation component with generated exposure, covariate, and outcome data inspired by a randomized intervention study. The simulation learner further generates various (linked) exposure types with a set of possible values per observation unit, from which observed as well as potential outcome data are generated. It thus provides true values of several causal effects. R code for data generation and analysis is available on www.ofcaus.org, where SAS and Stata code for analysis is also provided.
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What 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.