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Nathan T. T. Lau; Eric D. Wilkey; Mojtaba Soltanlou; Rebekka Lagacé Cusiac; Lien Peters; Paul Tremblay; Celia Goffin; Isabella Starling Alves; Andrew David Ribner; Clarissa Thompson; Jo Van Hoof; Julia Bahnmueller; Aymee Alvarez; Elien Bellon; Ilse Coolen; Fanny Ollivier; Daniel Ansari – Grantee Submission, 2022
During the COVID-19 pandemic, people across the globe have been exposed to large amounts of statistical data. Previous studies have shown that individuals' mathematical understanding of health-related information affects their attitudes and behaviours. Here, we investigate the relation between: (1) basic numeracy; (2) COVID-19 health numeracy; and…
Descriptors: Numeracy, COVID-19, Pandemics, Health Behavior
Gongjun Xu; Tony Sit; Lan Wang; Chiung-Yu Huang – Grantee Submission, 2017
Biased sampling occurs frequently in economics, epidemiology, and medical studies either by design or due to data collecting mechanism. Failing to take into account the sampling bias usually leads to incorrect inference. We propose a unified estimation procedure and a computationally fast resampling method to make statistical inference for…
Descriptors: Sampling, Statistical Inference, Computation, Generalization