mlsanityData to 7 Oct 2026

Bayesian Meta-Analyses Could Be More: A Case Study in Trial of Labor After a Cesarean-section Outcomes and Complications

arXiv 2601.10089 ↗First posted 15 Jan 2026cs.LGcited by 0

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Abstract (arXiv)

The meta-analysis's utility is dependent on previous studies having accurately captured the variables of interest, but in medical studies, a key decision variable that impacts a physician's decisions was not captured. This results in an unknown effect size and unreliable conclusions. A Bayesian approach may allow analysis to determine if the claim of a positive effect is still warranted, and we build a Bayesian approach to this common medical scenario. To demonstrate its utility, we assist professional OBGYNs in evaluating Trial of Labor After a Cesarean-section (TOLAC) situations where few interventions are available for patients and find the support needed for physicians to advance patient care.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 12 of its 70 references that are in the map. First posted on arXiv 15 Jan 2026.

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References · 12

  1. 2019Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyrocited by 187
  2. 2019A Step Toward Quantifying Independently Reproducible Machine Learning Researchcited by 77
  3. 2019The Sensitivity of Counterfactual Fairness to Unmeasured Confoundingcited by 35
  4. 2017Lasso Meets Horseshoe : A Surveycited by 17
  5. 2020Research Reproducibility as a Survival Analysiscited by 14
  6. 2023Reproducibility in Multiple Instance Learning: A Case For Algorithmic Unit Testscited by 11
  7. 2023Scaling Up Differentially Private LASSO Regularized Logistic Regression via Faster Frank-Wolfe Iterationscited by 8
  8. 2022A Siren Song of Open Source Reproducibilitycited by 7
  9. 2022Continuously Generalized Ordinal Regression for Linear and Deep Modelscited by 3
  10. 2022State Encoders in Reinforcement Learning for Recommendation: A Reproducibility Studycited by 3
  11. 2025Differentially Private Iterative Screening Rules for Linear Regressioncited by 2
  12. 2020Fixed-effects model: the most convincing model for meta-analysis with few studiescited by 1

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