Web-Based Lectures

Title: Survival Models for Spatial Data
Presenter: Benjamin M. Taylor, Lancaster University, UK
Date and Time: Tuesday, October 18, 2022, 11:00 a.m. – 1:00 p.m. ET (This course will be taught via Zoom)
Sponsor: Lifetime Data Science Section

Registration Deadline: Tuesday, October 18, at 10:30 a.m. Eastern time

Course Description:
Statistical methods for the analysis of survival data are not only applicable in the medical context, but also in many other areas of science and engineering. When survival times are spatially-referenced, some evidence of clustering of high or low times might be apparent on a visual inspection of the data. The question naturally arises as to whether these observed spatial survival patterns can be explained by incorporating appropriate covariates into the model or whether, in order to obtain reliable inferences for model parameters of interest, it is necessary to explicitly model the unexplained spatial variation. In this short course, we give an overview of spatial survival analysis: models, inference, and software and cover three applications of these techniques to real-world challenges.

Part 1 - Background and Review of Methodology

- An introduction to the modelling of spatial stochastic processes
- Combining spatial modelling with survival analyses
- Model selection
- Flexible parametric survival models
- Inference and software for fitting spatial survival models
- Extensions

Part 2 - Applications

Application 1: Modelling Survival in HIV Cohorts in Malawi
Application 2: Modelling Survival from Colorectal Cancer in Malaysia
Application 3: Spatial Modelling of Emergency Service Response Times

Registration Fees:
Lifetime Data Science Section Members: $20
ASA Members: $30
Student ASA Member: $25
Nonmembers: $45

Access Information

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