We need to talk about nonprobability samples [PDF]
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.
Robin J. Boyd +2 more
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Descriptive inference using large, unrepresentative nonprobability samples: An introduction for ecologists [PDF]
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 ...
Rob Boyd +2 more
+8 more sources
Fraud in Online Surveys: Evidence from a Nonprobability, Subpopulation Sample [PDF]
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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Integrating Probability and Nonprobability Samples for Survey Inference [PDF]
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 ...
Arkadiusz Wiśniowski +3 more
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Reconceptualizing Survey Representativeness for Evaluating and Using Nonprobability Samples [PDF]
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]
Dharma C +6 more
europepmc +2 more sources
Integration of Nonprobability and Probability Samples via Survey Weights
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
openalex +3 more sources
Comparing Alternatives for Estimation from Nonprobability Samples [PDF]
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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Supplementing Small Probability Samples with Nonprobability Samples: A Bayesian Approach [PDF]
Abstract Carefully designed probability-based sample surveys can be prohibitively expensive to conduct. As such, many survey organizations have shifted away from using expensive probability samples in favor of less expensive, but possibly less accurate, nonprobability web samples. However, their lower costs and abundant availability make
Joseph W. Sakshaug +3 more
openalex +3 more sources
Differences in Perceptions of Health Information Between the Public and Health Care Professionals: Nonprobability Sampling Questionnaire Survey. [PDF]
Gesser-Edelsburg A +6 more
europepmc +2 more sources

