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UID:fcf0efc56ce464b5ef214758dfabc814
DTSTAMP:20260517T062715Z
DTSTART:20251119T160000
DTEND:20251119T160000
SUMMARY:BEMC Talk: “Interpretational errors in causal inference and how to avoid them”
DESCRIPTION:📢 BEMC Talk: “Interpretational errors in causal inference and how to avoid them”\nThe BEMC series invites the community to a hybrid lecture on Wednesday, November 19, 2025, at 4:00 p.m. featuring Aaron Sarvet (University of Massachusetts Amherst, USA). 🌎📊\nIn his talk, Sarvet will explore how causal inference—originally rooted in practical, discipline-based questions—has evolved into a framework that now shapes which questions are asked and how evidence is interpreted. He will introduce the concept of “identity slippage,” an interpretational error increasingly observed in causal research, and demonstrate how recognizing this error is essential for sound public health and clinical decision-making. Case studies from mediation analysis and instrumental variable analysis will illustrate these challenges and their solutions. 🔍📈\n📍 In-person: Lecture Hall 21 (formerly Paul-Ehrlich-Hörsaal), Virchowweg 4, CCM
📝 Registration (in person): https://forms.gle/qZPpF8GTfqeqJ55p7\n💻 Online via Zoom: https://eu01web.zoom.us/webinar/register/WN_m-Sxmz6zQt-6RxDF7GxkFg
🌐 Not in Berlin? Join via livestream!\nA great opportunity for anyone interested in strengthening the bridge between causal theory, statistical interpretation, and real-world public health impact.
X-ALT-DESC;FMTTYPE=text/html:\n\n\n\n\n\n\n\n\n📢 BEMC Talk: “Interpretational errors in causal inference and how to avoid them”
The BEMC series invites the community to a hybrid lecture on Wednesday, November 19, 2025, at 4:00 p.m. featuring Aaron Sarvet (University of Massachusetts Amherst, USA). 🌎📊
In his talk, Sarvet will explore how causal inference—originally rooted in practical, discipline-based questions—has evolved into a framework that now shapes which questions are asked and how evidence is interpreted. He will introduce the concept of “identity slippage,” an interpretational error increasingly observed in causal research, and demonstrate how recognizing this error is essential for sound public health and clinical decision-making. Case studies from mediation analysis and instrumental variable analysis will illustrate these challenges and their solutions. 🔍📈
📍 In-person: Lecture Hall 21 (formerly Paul-Ehrlich-Hörsaal), Virchowweg 4, CCM
📝 Registration (in person): https://forms.gle/qZPpF8GTfqeqJ55p7
💻 Online via Zoom: https://eu01web.zoom.us/webinar/register/WN_m-Sxmz6zQt-6RxDF7GxkFg
🌐 Not in Berlin? Join via livestream!
A great opportunity for anyone interested in strengthening the bridge between causal theory, statistical interpretation, and real-world public health impact.
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