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Data Science Seminar Series – TRU Newsroom

Data Science Seminar Series – TRU Newsroom

March 1, 2021 at 3:47 pm  Education, Kamloops, News

Name:             Dr. Jabed Tomal, Dept. of Mathematics & Statistics, TRU

Title:               A Bayesian approach to accounting for survey weights in Poisson regression: Application to model the number of children ever born among married women of reproductive age in Bangladesh

Abstract: 

Poisson regression is used to assess the association between a count variable with explanatory variables. One of the main assumptions of standard Poisson regression is that the log of the mean count is a linear/nonlinear function of the explanatory variables. When data are collected using a simple random sampling, a traditional unweighted frequentist/Bayesian likelihood-based approach can be used for the inference. Survey data, on the other hand, generally report weights for the survey respondents which needs to be properly incorporated into the statistical model in order to ensure generalizability of the results. Motivated by the scope of incorporating weights in the Bangladesh Multiple Indicator Cluster Survey 2019 (MICS 2019) data, we proposed a Bayesian weighted Poisson regression model using the probabilistically defined weighted likelihood function. The method is illustrated using multiple prior distributions with the goal of applying shrinkage to the model parameters. We proposed the Metropolis algorithm to generate data from the posterior distribution of the parameters. The proposed model is compared with regular Bayesian Poisson regression model using a weighted Bayesian information criterion (Weighted BIC). Finally, we used our method to explain the number of children ever born among married women of reproductive age in Bangladesh using individual, societal, demographic factors from the Bangladesh MICS 2019 data.

Biography:

Dr. Jabed Tomal is an assistant professor in the Department of Mathematics and Statistics at TRU. He received his PhD in Statistical Machine Learning from the Department of Statistics at the University of British Columbia (UBC), Vancouver. Dr. Tomal holds two MSc degrees: one in Statistics from the Department of Mathematics and Statistics at the University of Windsor and the other in Biostatistics from the Department of Statistics at the University of Dhaka. Before joining TRU, he worked as an assistant professor at the University of Toronto at Scarborough and as a postdoctoral research fellow in the Department of Statistics at UBC. His research interest focuses on statistical machine learning, Bayesian statistical inference and statistical ecology with applications in drug discovery, protein homology, environmental ecology, and public health.

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