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TZID:America/Chicago
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DTSTART:20250309T030000
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DTSTART:20241103T010000
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BEGIN:VEVENT
DTSTAMP;TZID=America/Chicago:20260409T004111
UID:206414@calendar.wisc.edu
DTSTART;TZID=America/Chicago:20250228T131500
DTEND;TZID=America/Chicago:20250228T141500
DESCRIPTION:Kernel meets sieve: transformed hazards models with sparse long
 itudinal covariates. Dr. Cao proposes combining kernel-weighted log-likeli
 hood and sieve maximum log-likelihood estimation to conduct statistical in
 ference in a robust and easy-to-implement&nbsp\;method. Establishing the a
 symptotic properties of the proposed estimator contributes to a rigorous t
 heoretical framework for general kernel-weighted sieve M-estimators. The a
 nalysis of a data set from a COVID-19 study in Wuhan identifies clinical p
 redictors that cannot be obtained using existing methods.\n\nCONTACT: nach
 reiner3@wisc.edu\n\nURL: https://biostat.wisc.edu/events/special-seminars/
 \n\nONLINE: https://urldefense.com/v3/__https://teams.microsoft.com/l/meet
 up-join/19*3ameeting_MWIxZGE1YWEtYjhjNi00MDQyLTk2ZmUtYzQwZGMyYmVkOTU2*40th
 read.v2/0?context=*7b*22Tid*22*3a*222ca68321-0eda-4908-88b2-424a8cb4b0f9*2
 2*2c*22Oid*22*3a*2222f2aee8-03be-4bc2-8ac5-d5
LOCATION:1309 Health Sciences Learning Center  (Also offered online)
SUMMARY:Cancer Biostatistics Faculty Candidate Seminar - Hongyuan Cao\, PhD
 \, Florida State University
URL;VALUE=URI:https://biostat.wisc.edu/events/special-seminars/
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