Stata code: Additive and intersectional analyses for self-health concerns during the COVID-19 pandemic in Canada

Published: 2 September 2022| Version 1 | DOI: 10.17632/jwrdck627d.1
Laila Rahman


This repository includes two files: (1) a secondary data file with an analytical sample, "Rahman_2022_Covid19 AnalyticalSample_StatCanadaData2020" and (2) a Stata code file, "Rahman_2022_Covid19_StataCode" . Rahman (2022) wrote Stata code to analyse a sub-sample (N=239143) of Statistics Canada’s publicly available crowdsourcing data for findings presented in a book chapter. The purpose of this chapter was to showcase the contrast between additive and intersectional approaches to examine the COVID-19 impact on intersectional groups of Canadians. See Rahman's (2022) methods section and Supplemental Figure S1 in order to learn about this analytical sample. Statistics Canada (2020a) collected crowdsourcing data online from April 3 to 23, 2020 to understand the impacts of the COVID-19 pandemic in Canada. Statistics Canada’s (2020a; 2020b) publicly available complete data set and their documentation can be downloaded from REFERENCES Rahman, Laila. 2022. Concern for self-health during the COVID-19 pandemic in Canada: How to tell an intersectional story using quantitative data? In D. Woolford, D. Kotsopoulos, and B. Samuels (Eds.), Applied Data Science: Data Translators Across the Disciplines, Springer, Interdisciplinary Applied Sciences. (Accepted for publication). Statistics Canada. (2020a, June 3). Crowdsourcing: Impacts of COVID-19 on Canadians. Statistics Canada. (2020b). User guide for the crowdsourcing: Impacts of the COVID-19 on Canadians, public use microdata file.



Western University Schulich Dentistry


Data Analysis Computer Program, Secondary Data