BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Claremont Center for the Mathematical Sciences - ECPv6.15.17.1//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Claremont Center for the Mathematical Sciences
X-ORIGINAL-URL:https://colleges.claremont.edu/ccms
X-WR-CALDESC:Events for Claremont Center for the Mathematical Sciences
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/Los_Angeles
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20230312T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20231105T090000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20240310T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20241103T090000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20250309T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20251102T090000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240207T161500
DTEND;TZID=America/Los_Angeles:20240207T173000
DTSTAMP:20260406T235531
CREATED:20240201T010113Z
LAST-MODIFIED:20240201T010113Z
UID:3373-1707322500-1707327000@colleges.claremont.edu
SUMMARY:Shrinkage Estimation for Causal Inference and Experimental Design (Evan T. R. Rosenman)
DESCRIPTION:Title: Shrinkage Estimation for Causal Inference and Experimental Design \nSpeaker: Evan T. R. Rosenman\, Assistant Professor of Statistics\, Claremont McKenna College \nAbstract: Passive collection of observational data — in settings such as medicine\, insurance\, and e-commerce — is a ubiquitous feature of modern life. For statisticians\, these ever-proliferating datasets are both promising and perilous. Observational data often contain rich information about the causal effects of novel treatments\, such as a new vaccine or drug regimen. Yet\, because assignment to treatment is not randomized within these data\, one can never guarantee that treated and untreated units are comparable. Consequently\, causal effects derived from observational studies often suffer from bias. The applied literature contains myriad examples of treatments that seemed promising in observational data\, only to be overturned by later\, higher-quality studies. \nHow might we make headway\, given these challenges? One approach is to couple observational data with randomized trials. In this talk\, I will consider how to develop estimators to merge causal effect estimates obtained from observational and experimental datasets\, when the two data sources measure the same treatment. I will primarily operate in the Empirical Bayes (EB) framework. EB procedures\, rooted in the work of Charles Stein and the renowned James-Stein estimator\, offer principled\, data-driven methods for reconciling competing estimates of the same quantity. I will discuss two techniques for deriving EB estimators that effectively merge observational and experimental causal estimates. Additionally\, I will explore the potential contribution of these concepts to improving the efficiency of prospective randomized trials. Simple algorithms\, leveraging numerical integrals\, will be highlighted for making more informed recruitment and treatment assignment decisions within the experimental setup.\n\n\n\n\n\nEvan Rosenman is an Assistant Professor of Statistics in the Claremont McKenna Department of Mathematical Sciences. His research focuses primarily on problems in data science and causal inference\, with applications to political science and public health. He is particularly intrigued by problems involving hybridizing observational and experimental data to better estimate causal effects\, and by applications in modern electioneering\, such as ecological inference and prediction calibration. He earned his PhD in Statistics from Stanford University and completed a postdoctoral fellowship at the Harvard Data Science Initiative.
URL:https://colleges.claremont.edu/ccms/event/shrinkage-estimation-for-causal-inference-and-experimental-design-evan-t-r-rosenman/
LOCATION:Argue Auditorium\, Pomona College\, 610 N. College Ave.\, Claremont\, CA\, 91711\, United States
CATEGORIES:Colloquium
GEO:34.0999157;-117.7142668
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Argue Auditorium Pomona College 610 N. College Ave. Claremont CA 91711 United States;X-APPLE-RADIUS=500;X-TITLE=610 N. College Ave.:geo:-117.7142668,34.0999157
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240210T100000
DTEND;TZID=America/Los_Angeles:20240210T120000
DTSTAMP:20260406T235531
CREATED:20240123T234910Z
LAST-MODIFIED:20240123T234910Z
UID:3344-1707559200-1707566400@colleges.claremont.edu
SUMMARY:GEMS February 10th Session
DESCRIPTION:
URL:https://colleges.claremont.edu/ccms/event/gems-february-10th-session/
LOCATION:Harvey Mudd College at the Shanahan Teaching and Learning Center\, 301 Platt Blvd.\, Claremont\, CA\, 91711\, United States
CATEGORIES:GEMS
END:VEVENT
END:VCALENDAR