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SUMMARY:Simultaneous Directional Inference - Ruth Heller (Tel-Aviv Univers
 ity)
DTSTART:20230602T130000Z
DTEND:20230602T140000Z
UID:TALK199495@talks.cam.ac.uk
CONTACT:Qingyuan Zhao
DESCRIPTION:Joint work with Aldo Solari\n\nWe consider the problem of infe
 rence on the signs of n>1 parameters. Within a simultaneous inference fram
 ework\, we aim to: identify as many of the signs of the individual paramet
 ers as possible\; provide confidence bounds on the number of positive (or 
 negative) parameters on subsets of interest. Our suggestion is as follows:
  start by using the data to select the direction of the hypothesis test fo
 r each parameter\; then\, adjust the one-sided p-values for the selection\
 , and use them for simultaneous inference on the selected n one-sided hypo
 theses.\n\nThe adjustment is straightforward assuming that the one-sided p
 -values are conditionally valid and mutually independent. Such assumptions
  are commonly satisfied in a meta-analysis\, and we can apply our approach
  following a test of the global null hypothesis that all parameters are ze
 ro\, or of the hypothesis of no qualitative interaction. We consider the u
 se of two multiple testing principles: closed testing and partitioning. Th
 e novel procedure based on partitioning is more powerful\, but slightly le
 ss informative: it only infers on positive and non-positive signs. The pro
 cedure takes at most a polynomial time\, and we show its usefulness on a s
 ubgroup analysis of a medical intervention\, and on a meta-analysis of an 
 educational intervention. \n\nThe relevant paper is arXiv:2301.01653
LOCATION:MR11/B1.39\, Centre for Mathematical Sciences
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