A review of conceptual approaches and empirical evidence on probability and nonprobability sample survey research

Cornesse, Carina ; Blom, Annelies G. ; Dutwin, David ; Krosnick, Jon A. ; Leeuw, Edith D. de ; Legleye, Stéphane ; Pasek, Josh ; Pennay, Darren ; Phillips, Benjamin ; Sakshaug, Joseph W. ; Struminskaya, Bella ; Wenz, Alexander

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DOI: https://doi.org/10.1093/jssam/smz041
URL: https://madoc.bib.uni-mannheim.de/55064
Additional URL: https://academic.oup.com/jssam/article/8/1/4/56996...
URN: urn:nbn:de:bsz:180-madoc-550640
Document Type: Article
Year of publication: 2020
The title of a journal, publication series: Journal of Survey Statistics and Methodology : JSSAM
Volume: 8
Issue number: 1
Page range: 4-36
Place of publication: Oxford
Publishing house: Oxford Univ. Press
ISSN: 2325-0984 , 2325-0992
Related URLs:
Publication language: English
Institution: School of Social Sciences > Data Science (Blom 2017-2022)
Außerfakultäre Einrichtungen > SFB 884
Pre-existing license: Creative Commons Attribution, Non-Commercial 4.0 International (CC BY-NC 4.0)
Subject: 300 Social sciences, sociology, anthropology
Abstract: There is an ongoing debate in the survey research literature about whether and when probability and nonprobability sample surveys produce accurate estimates of a larger population. Statistical theory provides a justification for confidence in probability sampling as a function of the survey design, whereas inferences based on nonprobability sampling are entirely dependent on models for validity. This article reviews the current debate about probability and nonprobability sample surveys. We describe the conditions under which nonprobability sample surveys may provide accurate results in theory and discuss empirical evidence on which types of samples produce the highest accuracy in practice. From these theoretical and empirical considerations, we derive best-practice recommendations and outline paths for future research.

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