Survey Methodology
Comments by Aditi SenNote 1 on “Exploring the assumption that commercial online nonprobability survey respondents are answering in good faith”

  • Release date: June 25, 2024
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Abstract

This discussion summarizes the interesting new findings around measurement errors in opt-in surveys by Kennedy, Mercer and Lau (KML). While KML enlighten readers about “bogus responding” and possible patterns in them, this discussion suggests combining these new-found results with other avenues of research in nonprobability sampling, such as improvement of representativeness.

Key Words:  Opt-in survey; Measurement error; Data quality; Data integration; Inverse propensity score weighting.

How to cite

Sen, A. (2024). Comments on “Exploring the assumption that commercial online nonprobability survey respondents are answering in good faith”. Survey Methodology, Statistique Canada, n° 12‑001‑X au catalogue, vol. 50, n° 1. Paper available at http://www.statcan.gc.ca/pub/12-001-x/2024001/article/00010-eng.htm.

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ISSN : 1492-0921

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Survey Methodology publishes articles dealing with various aspects of statistical development relevant to a statistical agency, such as design issues in the context of practical constraints, use of different data sources and collection techniques, total survey error, survey evaluation, research in survey methodology, time series analysis, seasonal adjustment, demographic studies, data integration, estimation and data analysis methods, and general survey systems development. The emphasis is placed on the development and evaluation of specific methodologies as applied to data collection or the data themselves. All papers will be refereed. However, the authors retain full responsibility for the contents of their papers and opinions expressed are not necessarily those of the Editorial Board or of Statistics Canada.

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Published by authority of the Minister responsible for Statistics Canada.

© His Majesty the King in Right of Canada, as represented by the Minister of Industry, 2024

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Catalogue No. 12-001-X

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