ArticleAnnual review of sociology2023
Recent Developments in Causal Inference and Machine Learning.
Article in Annual review of sociology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- From association to causation: interpreting PS-based analyses in real-world evidence.Korean journal of anesthesiology · 2026Review
- How Advanced Artificial Intelligence Technologies Shape Drug-Drug and Drug-Target Interaction Modeling.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- A causal discovery framework for analyzing the impact mechanism of generative AI on digital literacy: an LLM-based behavioral analysis approach.Scientific reports · 2026Article
- SELF-Tree: An Interpretable Model for Multivariate Causal Direction Heterogeneity Analysis.Psychometrika · 2026Article
- Causal discovery methods in psychological research: Foundations, algorithms, and a practical tutorial in R.Behavior research methods · 2026Review
- Assimilative causal inference.Nature communications · 2026Article
- Machine Learning Prediction and Causal Forest Analysis of Severe Acute Kidney Injury in ICU Patients with COPD: A MIMIC-IV Study.International journal of chronic obstructive pulmonary disease · 2026Article
- Actigraphy and subjective sleep predictors of nine-year generalized anxiety disorder.Journal of anxiety disorders · 2026Article
- Causal machine learning uncovers conditions for convective intensification driven by organic and sulfate aerosols.Scientific reports · 2025Article
- Toward precision stroke rehabilitation: an integrated causal machine learning and clinician feedback approach.JAMIA open · 2025Article
- The causal effect of parent occupation on child occupation: A multivalued treatment with positivity constraints.Sociological methods & research · 2025Article
- Machine Learning Approaches for Geospatial Modeling of Urban Land Surface Temperature: Assessing Geographical Compactness, Interpretability, and Causal Inference.Sensors (Basel, Switzerland) · 2025Article
- An encoding generative modeling approach to dimension reduction and covariate adjustment in causal inference with observational studies.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- What really matters for global intergenerational mobility?PloS one · 2024Article
- Disparate Effects of Disruptive Events on Children.The Russell Sage Foundation journal of the social sciences : RSF · 2024Article
- Researcher reasoning meets computational capacity: Machine learning for social science.Social science research · 2022Review
- Causal Estimands and Multiply Robust Estimation of Mediated-Moderation.Multivariate behavioral researchArticle
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
This article reviews recent advances in causal inference relevant to sociology. We focus on a selective subset of contributions aligning with four broad topics: causal effect identification and estimation in general, causal effect heterogeneity, causal effect mediation, and temporal and spatial interference. We describe how machine learning, as an estimation strategy, can be effectively combined with causal inference, which has been traditionally concerned with identification. The incorporation of machine learning in causal inference enables researchers to better address potential biases in estimating causal effects and uncover heterogeneous causal effects. Uncovering sources of effect heterogeneity is key for generalizing to populations beyond those under study. While sociology has long emphasized the importance of causal mechanisms, historical and life-cycle variation, and social contexts involving network interactions, recent conceptual and computational advances facilitate more principled estimation of causal effects under these settings. We encourage sociologists to incorporate these insights into their empirical research.
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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.