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

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Authors

Cornesse, Carina
Blom, Annelies G.
Dutwin, David
Krosnick, Jon A.
De Leeuw, Edith D.
Legleye, Stephane
Pasek, Josh
Pennay, Darren
Phillips, Ben
Sakshaug, Joseph W.

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Oxford University Press

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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Journal of Survey Statistics and Methodology

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Open Access

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Creative Commons Attribution Non-Commercial License

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