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Home » Social and Health Survey Data Sources and Emerging Data Collection Methods

Social and Health Survey Data Sources and Emerging Data Collection Methods

Short Course, Spring Seminar Series, Institute for Social Research, York University

Instructor: Hugh McCague

9:00am-12:30pm, Tuesday, May 16, 2023
Zoom Meeting

Resource Web Links for the Course

1. Statistics Canada

1.1 Statistics Canada
http://www.statcan.gc.ca/

1.2 Select Statistics Canada Surveys, Statistics Canada Research Data Centre at McMaster University
https://rdc.mcmaster.ca/data-files

1.3 All DLI Products, Data Liberation Initiative (DLI)
http://www.statcan.gc.ca/dli-ild/products-eng.htm

2. Statistics Canada Research Data Centres (RDCs) and the York RDC (York University RDC)

2.1 The York University Statistics Canada Research Data Centre (RDC)
https://www.yorku.ca/research/isr/centres/statistics-canada-research-data-centre/

 2.2 Research Data Centres (RDCs), Statistics Canada
https://www.statcan.gc.ca/en/microdata/data-centres

2.3 RDC Data, Statistics Canada
http://www.statcan.gc.ca/eng/rdc/data

2.4 Canadian Research Data Centre Network (CRDCN) (including information on RDC data)
https://crdcn.ca/

2.5 Application process and guidelines for research projects at RDCs
http://www.statcan.gc.ca/eng/rdc/process

2.6 SSHRC Web-based Forms: Registration and Logon
https://webapps.nserc.ca/SSHRC/faces/logon.jsp?lang=en_CA

3. Data Resources and Searching for Data

3.1 Data & Statistics Library Guide, York University Libraries (YUL)
http://researchguides.library.yorku.ca/data

3.2 <odesi>, Ontario Council of Libraries (OCUL)
http://www.library.yorku.ca/e/resolver/id/1165738  (for York U. community members)

3.3 <odesi>, Ontario Council of Libraries (OCUL)
http://odesi.ca/  (for non-York U. users)

3.4 CHASS Data Centre, Computing in the Humanities and Social Sciences (CHASS), University of Toronto
http://datacentre2.chass.utoronto.ca/ (for subscribers including York University)

3.5 Abacus Data Network,
https://abacus.library.ubc.ca/dataverse/open

4. Data Equity

4.1 We All Count
https://weallcount.com/

5. York University Data

5.1 Data Hub, OIPA, York University
https://oipa.info.yorku.ca/data-hub/

6. International Data

6.1 DHS (Demographic and Health Surveys)
https://dhsprogram.com/data/available-datasets.cfm

6.2 ICPSR (Inter-university Consortium for Political and Social Research)
http://www.icpsr.umich.edu/icpsrweb/

6.3 IPUMS (Integrated Public Use Microdata Series)
https://www.ipums.org/

6.4 UK Data Service
https://www.ukdataservice.ac.uk/get-data/key-data

6.5 World Bank Microdata Library
http://microdata.worldbank.org/index.php/home

6.6 PISA Database
http://www.oecd.org/pisa/data/

6.7 World Values Survey
http://www.worldvaluessurvey.org/

6.8 International Social Survey Program
https://issp.org/

6.9 Eurostat
https://ec.europa.eu/eurostat

7. Social Media, Web Scraping, Text Mining, Google Searches, and Wiki Surveys

7.1 Prof. Matthew Salganik's resources on social networks and computational social science
http://www.princeton.edu/~mjs3/

7.2 Salganik, Matthew J. Bit by Bit: Social Research in the Digital Age. Princeton: Princeton University Press, 2018.
Publisher’s information: https://press.princeton.edu/books/paperback/9780691196107/bit-by-bit 

7.3 Munzert, Simon et al. Automated Data Collection with R: A Practical Guide to Web Scraping and Text Mining. Wiley, 2015.
http://www.r-datacollection.com/

7.4 Interview with John Dagdelen, “AI is reviewing scientists' old work and discovering things they missed”
https://www.cbc.ca/radio/quirks/nov-9-lionfish-are-super-digesters-voyager-2-goes-interstellar-carbon-capture-and-more-1.5352117/ai-is-reviewing-scientists-old-work-and-discovering-things-they-missed-1.5352128

7.5 John Dagdelen, “Natural Language Processing for Materials Discovery and Design”
https://www.youtube.com/watch?v=l8YVmVwLFhQ

7.6 John Dagdelen et al., “Unsupervised word embeddings capture latent knowledge from materials science literature

7.7 DiGrazia J., McKelvey K., Bollen J., Rojas F. “More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior.” PLoS ONE 8.11 (2013): e79449.
https://doi.org/10.1371/journal.pone.0079449

7.8 Advanced Symbolics Inc., Ottawa: an example of using AI and social media for public opinion, survey and market research
https://www.advancedsymbolics.com/

7.9 "Using AI to prevent suicide in First Nations communities," Advanced Symbolics Inc.
https://advancedsymbolics.com/using-ai-to-prevent-suicide-in-first-nations-communities/

7.10 “Margin of Error,” TVOntario Documentary on political polling, AI, and Advanced Symbolics Inc.
https://www.tvo.org/video/documentaries/margin-of-error

7.11 Google Trends
https://trends.google.com/trends/

7.12 Google Ads, fee-based
https://ads.google.com/intl/en_ca/home/

7.13 Dr. Seth Stephen-Davidowitz's resources on using Google Trends and Google Ads
http://www.sethsd.com

7.14 Research on Refugees using Google Trends, Pew Research Center
https://www.pewresearch.org/global/2017/06/08/online-searches-eu-refugees-methodology/

7.15 Lu, T., Reis, B.Y. “Internet search patterns reveal clinical course of COVID-19 disease progression and pandemic spread across 32 countries.” npj Digit. Med. 4,22 (2021).
https://doi.org/10.1038/s41746-021-00396-6

7.16 All Our Ideas Project, Prof. Matthew Salganik: an adaptive wiki survey
https://www.allourideas.org/

7.17 Salganik MJ, Levy KEC. “Wiki Surveys: Open and Quantifiable Social Data Collection.” PLoS ONE 10.5 (2015): e0123483. https://doi.org/10.1371/journal.pone.0123483

8. Data from Wearables and Surveys using Cell Phones

8.1 Ben Cornish, "Wearable Sensors and Health Monitoring" overview, Ontario Neurodegenerative Disease Research Initiative (ONDRI)
https://www.youtube.com/watch?v=siKRu50KA4o

8.2 "Volumes of Survey Data Provide Valuable Insights into Vaccine Hesitancy," National Institute of Statistical Sciences (NISS)
https://www.niss.org/news/volumes-survey-data-provide-valuable-insights-vaccine-hesitancy

9. Survey Research Methods

9.1 Ornstein, Michael. A Companion to Survey Research. London; Thousand Oaks, CA: SAGE, 2013.
Publisher’s information: https://us.sagepub.com/en-us/nam/a-companion-to-survey-research/book237402

10. Survey Weights

10.1 Statistics Canada, “Weighted estimation and bootstrap variance estimation for analyzing survey data: How to implement in selected software”
http://www.statcan.gc.ca/pub/12-002-x/2014001/article/11901-eng.htm

10.2 A worked example of a statistical analysis using bootstrap weights in Stata
http://www.isr.umich.edu/src/smp/asda/Additional%20Stata%20Examples%20svy%20bootstrap.pdf

10.3 Rebekah Young and David R. Johnson, "To Weight or Not to Weight, That is the Question: Survey Weights and Multivariate Analysis"
https://www.aapor.org/AAPOR_Main/media/AnnualMeetingProceedings/2012/03_-Young-Johnson_A2_Weighting-paper_aapor-2012-ry.pdf

11. Statistical Resources

11.1 Statistical Software Resources, Institute for Digital Research and Educations (idre), UCLA
https://stats.idre.ucla.edu/

11.2 Statistical Consulting Service, York University
http://www.isr.yorku.ca/scs/

12. Causality

12.1 Pearl, Judea and Mackenzie, Dana. The Book of Why: The New Science of Cause and Effect. New York: Basic Books, 2018. A non-scholarly book aiming to make Pearl’s scholarly and technical work on causality more accessible to the general reader. http://bayes.cs.ucla.edu/WHY/