A Review of Conceptual Approaches and Empirical Evidence on Probability and Nonprobability Sample Survey Research
Year: 2019
Type: article
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.
DOI: 10.1093/jssam/smz041
Institutions: University of Mannheim, University of Chicago, National Opinion Research Center, Stanford University, Utrecht University, Université Paris-Sud, Institut National de la Statistique et des Etudes Economiques, Inserm, Université de Versailles Saint-Quentin-en-Yvelines, Université Paris-Saclay, Centre de recherche en Epidémiologie et Santé des Populations, University of Michigan, Institute for Social Research, Australian National University, The University of Queensland, Institut für Arbeitsmarkt und Berufsforschung, Ludwig-Maximilians-Universität München
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,472
Awards: G1450655456, G2228243831
OpenAlex ID: W3000214403