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BEGIN:VEVENT
DTSTAMP:20260609T145618Z
DTSTART;VALUE=DATE-TIME:20260127T140000
DTEND;VALUE=DATE-TIME:20260127T150000
SUMMARY:CRiSM - First Colloquium by Daniela Witten about Valid F-screenin
 g in linear regression
TZID:Europe/London
UID:20260127-8ac672c7993d982501993e6497730495@warwick.ac.uk
CREATED:20260105T092050Z
DESCRIPTION:Daniella Witten (https://www.danielawitten.com/)\, COPSS awar
 dee\, current co-editor of JRSSB. Research interests: statistical machin
 e learning\, biostats\, etc. Suppose that a data analyst wishes to repor
 t the results of a least squares linear regression only if the overall n
 ull hypothesis—namely\, that all non-intercept coefficients equal zero—i
 s rejected. This practice\, which we refer to as F-screening (since the 
 overall null hypothesis is typically tested using an F-statistic)\, is i
 n fact common practice across a number of applied fields. Unfortunately\
 , it poses a problem: standard guarantees for the inferential outputs of
  linear regression\, such as Type 1 error control of hypothesis tests an
 d nominal coverage of confidence intervals\, hold unconditionally\, but 
 fail to hold conditional on rejection of the overall null hypothesis. In
  this talk\, I will present an inferential toolbox for the coefficients 
 in a least squares model that are valid conditional on rejection of the 
 overall null hypothesis. I will present selective p-values that lead to 
 tests that control the selective Type 1 error\, i.e.\, the Type 1 error 
 conditional on having rejected the overall null hypothesis. Furthermore\
 , they can be computed without access to the raw data\, using only the s
 tandard outputs of a least squares linear regression\, and therefore are
  suitable for use in a retrospective analysis of a published study. I wi
 ll also present confidence intervals that attain nominal selective cover
 age\, and point estimates that account for having rejected the overall n
 ull hypothesis. I will illustrate this selective procedure via re-analys
 is of a published result in the biomedical literature\, for which the ra
 w data is not available. This is joint work with Olivia McGough (U. Wash
 ington) and Daniel Kessler (UNC Chapel Hill).
LOCATION:Zeeman Building MS.04
CATEGORIES:CRiSM Seminars,Seminars,Dept,Colloquium,CRiSM
LAST-MODIFIED:20260105T092050Z
ORGANIZER;CN=Kathrin Schutrumpf:
END:VEVENT
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