We need to talk about nonprobability samples [PDF]
Trends in Ecology & Evolution, 2023 In most circumstances, probability sampling is the only way to ensure unbiased inference about population quantities where a complete census is not possible. As we enter the era of 'big data', however, nonprobability samples, whose sampling mechanisms are unknown, are undergoing a renaissance.
Boyd, Robin J. +2 more
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Descriptive inference using large, unrepresentative nonprobability samples: An introduction for ecologists [PDF]
Ecology, 2023 AbstractBiodiversity monitoring usually involves drawing inferences about some variable of interest across a defined landscape from observations made at a sample of locations within that landscape. If the variable of interest differs between sampled and nonsampled locations, and no mitigating action is taken, then the sample is unrepresentative and ...
Boyd, Robin J. +2 more
+8 more sources
Integrating Probability and Nonprobability Samples for Survey Inference [PDF]
Journal of Survey Statistics and Methodology, 2020 Abstract Survey data collection costs have risen to a point where many survey researchers and polling companies are abandoning large, expensive probability-based samples in favor of less expensive nonprobability samples. The empirical literature suggests this strategy may be suboptimal for multiple reasons, among them that probability ...
Wiśniowski, Arkadiusz +3 more
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Fraud in Online Surveys: Evidence from a Nonprobability, Subpopulation Sample [PDF]
SSRN Electronic Journal, 2021 AbstractWe hired a well-known market research firm whose surveys have been published in leading political science journals, including JEPS. Based on a set of rigorous “screeners,” we detected what appears to be exceedingly high rates of identity falsification: over 81 percent of respondents seemed to misrepresent their credentials to gain access to the
Andrew M. Bell, Thomas Gift
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Reconceptualizing Survey Representativeness for Evaluating and Using Nonprobability Samples [PDF]
Survey Practice, 2013 A question in recent times has been the quality of surveys using nonprobability samples. This paper approaches measurement accuracy by reconceptualizing representativeness. This approach can be used for all samples, probability or not. Current survey designs aim for representative samples with the implicit assumptions that representativeness belongs to
David P. Fan
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A two-step approach to simultaneously correct for selection and misclassification bias in nonprobability samples from hard-to-reach populations. [PDF]
Am J EpidemiolDharma C +6 more
europepmc +2 more sources
Correction for Participation Bias in Nonprobability Samples Using Multiple Reference Surveys. [PDF]
Stat MedLandsman V +7 more
europepmc +2 more sources
Comparing Alternatives for Estimation from Nonprobability Samples [PDF]
Journal of Survey Statistics and Methodology, 2019 AbstractThree approaches to estimation from nonprobability samples are quasi-randomization, superpopulation modeling, and doubly robust estimation. In the first, the sample is treated as if it were obtained via a probability mechanism, but unlike in probability sampling, that mechanism is unknown.
Richard Valliant
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Integration of Nonprobability and Probability Samples via Survey Weights
International Journal of Statistics and Probability, 2021 Probability sample encounters the problems of increasing cost and nonresponse. The cost has rapidly been increasing in executing a large probability sample survey, and, for some surveys, response rate can be below the 10 percent level. Therefore, statisticians seek some alternative methods.
Balgobin Nandram, Jai Won Choi, Yang Liu
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Differences in Perceptions of Health Information Between the Public and Health Care Professionals: Nonprobability Sampling Questionnaire Survey. [PDF]
J Med Internet Res, 2019 Gesser-Edelsburg A +6 more
europepmc +2 more sources