New Developments in Causal Inference with Applications in Healthcare and Economics
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Probability and Statistics".
Deadline for manuscript submissions: 31 December 2024 | Viewed by 219
Special Issue Editors
Interests: biostatistics; computation statistics; EM algorithms; joint models; multiple imputation; event history analysis; causal inference
Special Issue Information
Dear Colleagues,
We invite researchers and scholars to submit their research papers for our Special Issue on “New Developments in Causal Inference with Applications in Healthcare and Economics”. Causal inference has emerged as a crucial area of research, enabling us to uncover causal relationships and make informed decisions across various domains. This interdisciplinary field holds immense potential for advancing our understanding and enhancing evidence-based practices in healthcare, economics and social sciences. We invite researchers and practitioners to contribute original research, reviews, and case studies that showcase recent advancements in causal inference methods with applications in those domains where the topics of interest include but are not limited to the following: propensity score matching and weighting; instrumental variables and regression discontinuity designs; causal machine learning and deep learning approaches; counterfactual estimation and causal mediation analysis; Bayesian causal inference and sensitivity analysis; time series causal modelling and causal forecasting; transfer learning and causal domain adaptation; and causal graphs and structural equation modelling.
Dr. Hongbin Zhang
Dr. Ang Li
Guest Editors
Manuscript Submission Information
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Keywords
- propensity score
- double robustness
- counterfactual estimation
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Planned Papers
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Probability of Causation with Infinity Counterfactual Terms
Authors: Ang Li
Affiliation: Florida State University
Title: Doubly robust quantile estimate for observational clinical trial
Authors: Ao Yuan
Affiliation: Georgetown University
Title: Is High-Dimensionality a Cure-All? Reevaluating Model Specification in the High-dimensional Propensity Score Models
Authors: Ehsan Karim
Affiliation: University of British Columbia
