Antonio Remiro-Azócar, PhD
  • Bio
  • Experience
  • Papers
  • Talks
  • Projects
  • Projects
    • Pandas
    • PyTorch
    • scikit-learn
  • Experience
  • Blog
    • 🎉 Easily create your own simple yet highly customizable blog
    • 🧠 Sharpen your thinking with a second brain
    • 📈 Communicate your results effectively with the best data visualizations
    • 👩🏼‍🏫 Teach academic courses
    • ✅ Manage your projects
  • Publications
    • Doubly robust augmented weighting estimators for the analysis of externally controlled single-arm trials and unanchored indirect treatment comparisons
    • Effect modification and non-collapsibility together may lead to conflicting treatment decisions: A review of marginal and conditional estimands and recommendations for decision-making
    • Estimands and their implications for evidence synthesis for oncology: A case study of treatment switching in meta-analysis
    • The ICH E9 (R1) Estimand Framework in the Context of Real-World Data and Observational Studies
    • Transportability of model-based estimands in evidence synthesis
    • Broad versus narrow research questions in evidence synthesis: A parallel to (and plea for) estimands
    • Estimands and Strategies for Handling Treatment Switching As an Intercurrent Event in Evidence Synthesis of Randomized Clinical Trials in Oncology
    • Model-based standardization using multiple imputation
    • Estimands in Health Technology Assessments - Methodological Considerations and Recommendations
    • Methodological considerations for novel approaches to covariate-adjusted indirect treatment comparisons
    • Some considerations on target estimands for health technology assessment
    • Target estimands for population-adjusted indirect comparisons
    • Two-stage matching-adjusted indirect comparison
    • Parametric G-computation for compatible indirect treatment comparisons with limited individual patient data
    • Population-adjusted indirect treatment comparisons with limited access to patient-level data
    • Effect modification in anchored indirect treatment comparison - Comments on “Matching-adjusted indirect comparisons - Application to time-to-event data”
    • Comparison of Parametric Survival Extrapolation Approaches Incorporating General Population Mortality for Adequate Health Technology Assessment of New Oncology Drugs
    • Methods for population adjustment with limited access to individual patient data - A review and simulation study
    • Assessing the Impact of Modeling Non-Disease-Related Mortality on Long-Term Survivorship Rates in Previously Untreated Advanced Melanoma - A Case Study from CheckMate 067
    • Conflating marginal and conditional treatment effects - Comments on “Assessing the performance of population adjustment methods for anchored indirect comparisons - A simulation study”
    • Estimating long-term survivorship in patients with advanced melanoma treated with immune-checkpoint inhibitors - Analyses from the phase III CheckMate 067 trial
    • Marginalization of Regression-Adjusted Treatment Effects in Indirect Comparisons with Limited Patient-Level Data
    • Predictive-adjusted indirect comparison (PAIC) - a novel method for population-adjusted indirect comparison
  • Recent Talks
    • Considerations for Methodological Innovation for Indirect Treatment Comparisons in Pan-European HTA
    • Health technology assessments and the role of statisticians
    • Advanced Methods for Matching-Adjusted Indirect Comparison
    • Indirect treatment comparisons - choosing the right tool for the job
    • Estimands, PICOs and Co. - Are we losing or gaining in translation?
    • Apples and oranges in the context of indirect treatment comparisons
    • Marginalization of regression-adjusted treatment effects for compatible indirect comparisons
  • Teaching
    • Learn JavaScript
    • Learn Python

scikit-learn

Oct 26, 2023 · 1 min read
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scikit-learn is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license.

Last updated on May 19, 2024
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Antonio Remiro-Azócar
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Antonio Remiro-Azócar
Statistical Innovation Leader
← PyTorch Oct 26, 2023

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