Creation of the first national linked colorectal cancer dataset in Scotland: prospects for future research and a reflection on lessons learned
This webinar is part of the Power of Population Data Science Series
In this webinar, Peter, Catherine, Elizabeth and Steve will be describing their recent efforts to create the first national linked colorectal cancer (CRC) database in Scotland (full details in their recent publication).
Population-based Models for COVID-19 Hospitalization Forecast in British Columbia
This webinar is part of the Advanced Methods Webinar Series
The outbreaks of COVID-19 have posed a significant pressure on the health care system. There is therefore a great demand to predict which cases are likely to require hospitalization, to in turn identify hospitals most at-risk of being overwhelmed should such an outbreak occur.
The BC Provincial Overdose Cohort
The Call for Proposals to access the Provincial Overdose Cohort is currently closed.
Data source: Various

Date range:
Cases start from January 1, 2015 and end on December 31st, 2019
Marginal Structural Models
This webinar is part of the Advanced Methods Webinar Series
Health administrative data is longitudinal with measures captured on individuals over time. Conventional regression-based methods applied to longitudinal data do not explicitly account for time-varying confounders and can produce biased estimates for causal effects.
What is the burden of Cystic Fibrosis in BC?

Cystic Fibrosis (CF) is one of the most common fatal genetic diseases affecting Canadians. Thick mucus in the airways, a hallmark of CF, prevents clearance of pathogens from the lungs, resulting in irreversible destruction of the airways over-time, and leads to respiratory failure and premature death.
Introduction to R
Session 1: Tuesday April 6 | Session 2: Thursday April 8
Session 3: Tuesday April 13 | Session 4: Thursday April 15
Overview
R is rapidly growing adoption through research and government institutions. R is a free software program and most RStudio products are free as well with no monthly subscriptions or licensing costs.
Use of Causal Diagrams in Variable Selection for Causal Observational Studies
This webinar is part of the Advanced Methods Webinar Series
Deciding which variables to adjust for when addressing causal questions in observational studies can be challenging. For example, lack of adjustment for some variables might lead to sub-optimal control for confounding whereas overadjustment for other variables can in fact introduce bias to a study.
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