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UID:20250726T090251EDT-9281p1F4xg@132.216.98.100
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DESCRIPTION:Edward Bein\, PhD\n\nSenior Statistician\n\nWhere: In-person | 
 2001 91������ College Avenue\, room 1140\; Zoom\n\nNote: Social gathering (O
 pen area outside Rm1140) from 3-3:30pm\n\nAbstract\n\nThe US Food and Drug
  Administration increasingly emphasizes the importance of assessing how pa
 tients “feel\, function\, and survive” when evaluating new treatments in c
 linical trials\, often via the use of endpoints derived from patient-repor
 ted outcome measures (PROs). This presentation examines possible pitfalls 
 in using PRO-derived endpoints to estimate and test hypotheses about treat
 ment effects. It discusses the notion of whether endpoints possess “causal
  inference validity\,” and presents inferential remedies when such validit
 y is not achieved. The pitfalls and remedies are exemplified in a simulati
 on study using the Rasch item response theory measurement model to analyze
  a PRO.\n\nSpeaker Bio\n\nEd Bein is on sabbatical from the US Food and Dr
 ug Administration\, where he is a senior statistician at the Center for Dr
 ug Evaluation and Research. He has reviewed randomized trials evaluating t
 reatments for infectious diseases\, including COVID-19 and observational s
 tudies of the long-term safety of recently approved drugs. He has a Ph.D. 
 in biostatistics from UC Berkeley and was a clinical psychologist in his p
 revious career.\n
DTSTART:20230308T203000Z
DTEND:20230308T213000Z
SUMMARY:The psychometrics of clinical trial endpoints derived from patient-
 reported outcome measures: Causal inference validity
URL:/epi-biostat-occh/channels/event/psychometrics-cli
 nical-trial-endpoints-derived-patient-reported-outcome-measures-causal-inf
 erence-345893
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