Related Experiment Video
Updated: Nov 8, 2025

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Quasi-Simpson paradox in estimating the expected mortality rate from the SARS-CoV-2
1Jerusalem College of Technology, Jerusalem, Israel.
Abstract:
On January 30, 2020, the World Health Organization (WHO) declared SARS-CoV-2 a global pandemic, based on a high infection rate and a high case fatality rate (CFR). The combination of these two points led WHO to forecast a high expected mortality rate of approximately 2% of the population. The phenomenon of Simpson's paradox teaches us that we should be careful when we combine two variables together. Indeed, despite the high mortality rate in several places, this forecast seems to have collapsed. We believe one of the reasons for the erroneous forecasts is that combining the above points ignored a confounding variable - many of the virus carriers are asymptomatic and therefore not diagnosed.
More Related Videos
Related Concept Videos
Actuarial Approach
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Kaplan-Meier Approach
Assumptions of Survival Analysis
Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Bias in Epidemiological Studies
Causality in Epidemiology

