Join Shabnam Balamchi, a PhD student from the University of Manitoba for her talk on Thursday, February 4th about “Repeated Events in Spatial Count Data with an Application to Disease Mapping”.


Mixed models are commonly used to analyze spatial data which frequently occur in practice such as in health sciences and life studies. It is customary to incorporate spatial random effects into the model to account for spatial variation of the data. In particular, Poisson mixed models are used to analyze spatial count data. It is often assumed that the observations in each area, conditional on the spatial random effects, are independent of each other. However, this may not be a valid assumption in practice. For instance, multiple asthma visits by a child to physicians (within a year) are not clearly independent observations. To address this issue, we develop spatial models with repeated events. In particular, compound Poisson mixed models are introduced to account for the repeated events as well as the spatial variation of the data. Performance of the proposed approach is evaluated through simulation studies and by a real dataset of children asthma visits to physicians in the province of Manitoba, Canada.

DATE: Thursday, February 4th, 2021

WHERE: Zoom (see below for more information)

WHEN: 2:30pm

If you wish to attend a Statistics Seminar please contact Po Yang ( or Leah Phillips ( from the U of M’s Statistics Department for more details and Zoom meeting information.

Jan 25, 2021