Hierarchical linear model with power law function on transmission of COVID-19 in Italy: Modelling and regression analysis

Youtian Hao (UNB Fredericton)

COVID-19 growth data were typically collected from each region of a country, and the transmission rate usually varies in different area. By adopting a power law with exponential cutoff function into hierarchical linear model, it becomes possible to reveal the relationship between COVID-19 transmission rate and some regional level covariates of interest. A two-level hierarchical linear model is constructed, where the first level includes a PLEC function with Poisson link, and the second level incorporates parameters from level-one with regional level covariates. Modelling and regression analysis approach is implemented based on the model with Italian COVID-19 transmission data.

Why Most Published Research Findings Are False

Hugh Chipman (Acadia)

Many scientific studies declare a “statistically significant” result but then can’t be replicated. What’s going on? Can we no longer trust statistics? Is this the end of the world as we know it?

Musical Guests

• Michele Millar (MSVU)
• Augusto Suarez Garcia (UNBSJ)

This is a virtual zoom meeting.  If you would like to attend, please email the organizers for connection details.

[more information about the Math Kitchen Party summer talk series]