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DTSTAMP:20261105T001421Z
DESCRIPTION:Alex Stringer\, PhD\n\nAssistant Professor\n	Department of Stati
 stics and Actuarial Science |\n	University of Waterloo\n\nWHEN: Wednesday\,
  October 23\, 2024\, from 3:30 to 4:30 p.m.\n	WHERE: Hybrid | 2001 McGill C
 ollege Avenue\, Room 1201\; Zoom\n	NOTE: Alex Stringer will be presenting i
 n-person\n\nAbstract\n\nI discuss two new methods involving additive model
 s that are relevant to environmental epidemiology and toxicology. The firs
 t is a new cumulative exposure additive model for overdispersed count data
  in which the covariate being smoothed is the integrated weighted exposure
  to a pollutant. The weight function and the regression function are both 
 unknown and modelled using penalized splines. The method is used to analyz
 e several years of daily health outcome counts and their association with 
 cumulative exposure to three air pollutants in various regions across Cana
 da\, as part of an active collaboration with Health Canada in support of t
 he Air Health Trend Indicator project. The second is a new approach to the
  determination of allowable doses in environmental toxicology. The dose-re
 sponse curve is fit using monotone splines and the benchmark dose and lowe
 r limit are obtained using fast implementations of Newton's method that ma
 ke use of de Boor's algorithm for spline curve evaluation. The method is a
 pplied to the study of prenatal alcohol exposure and child cognition using
  data from six NIH-funded longitudinal cohort studies. The common theme of
  efficient computation with splines unites these two seemingly unrelated m
 ethodologies. If time permits\, I will also discuss ongoing efforts to dev
 elop general hypothesis tests for linearity in multiple-component additive
  models and of zero variance components in random effects models more gene
 rally. Based on joint work with Tianyi Pan\, Glen McGee\, Tugba Akkaya Hoc
 agil\, Richard Cook\, Louise Ryan\, Sandra and Joseph Jacobson\, and Jeffr
 ey Negrea.\n\nSpeaker bio\n\nPlease visit: https://alexstringer.ca\n
DTSTART:20241023T193000Z
DTEND:20241023T203000Z
SUMMARY:Two New Methods for Nonlinear Regression in Epidemiology and Enviro
 nmental Toxicology
URL:https://www.mcgill.ca/epi-biostat-occh/channels/event/two-new-methods-n
 onlinear-regression-epidemiology-and-environmental-toxicology-359784
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