Combining Data & Making Effects Generalizable with Carly Brantner | Season 6 Episode 7

Casual Inference

Carly Brantner is an assistant professor of Biostatistics & Bioinformatics at Duke University and Duke Clinical Research Institute.

Resources from this episode:
  • multicate: R package for estimating conditional average treatment effects across one or more studies using machine learning methods
  • PCORnet® Front Door: Access point for potential investigators, patient groups, and other stakeholders to connect with PCORnet and get support for potential research studies
  • Patient-Centered Outcomes Data Repository (PDOCR): De-identified data from 24 (and counting) PCORI-funded studies
Follow along on Bluesky:   🎶 Our intro/outro music is courtesy of Joseph McDade. Edited by Cameron Bopp.
More description

Carly Brantner is an assistant professor of Biostatistics & Bioinformatics at Duke University and Duke Clinical Research Institute.

Resources from this episode:
  • multicate: R package for estimating conditional average treatment effects across one or more studies using machine learning methods
  • PCORnet® Front Door: Access point for potential investigators, patient groups, and other stakeholders to connect with PCORnet and get support for potential research studies
  • Patient-Centered Outcomes Data Repository (PDOCR): De-identified data from 24 (and counting) PCORI-funded studies
Follow along on Bluesky:   🎶 Our intro/outro music is courtesy of Joseph McDade. Edited by Cameron Bopp.
2025-06-17 52 min
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