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
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Correction for Participation Bias in Nonprobability Samples Using Multiple Reference Surveys. [PDF]
Stat MedLandsman V +7 more
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Annual Review of SociologyOnline nonprobability samples provide social scientists with opportunities to conduct surveys and experiments on large, diverse samples at modest prices. Researchers may find bewildering the options offered by the many commercial entities that provide research participants, and our review seeks to orient researchers to key issues about their use.
Jeremy Freese, Olivia Jin
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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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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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Data integration with nonprobability sample: Semiparametric model‐assisted approach [PDF]
Scandinavian Journal of StatisticsAbstract This paper introduces a novel semiparametric model‐assisted estimation method that integrates data from both probability and nonprobability samples, thereby facilitating robust and efficient inferences regarding finite population parameters.
Danhyang Lee, Sixia Chen
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A Demonstration of Propensity-Score Weighting to Adjust a Social Media Nonprobability Sample Survey of Political Attitudes. [PDF]
Public Opin QPollard MS, Robbins MW, Griswold M.
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occAssess: An R package for assessing potential biases in species occurrence data
Ecology and Evolution, 2021 Species occurrence records from a variety of sources are increasingly aggregated into heterogeneous databases and made available to ecologists for immediate analytical use. However, these data are typically biased, i.e.
Robin J. Boyd +3 more
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Survey Research Methods, 2022 In this paper we report the findings from our study which was undertaken to learn if the findings of Chang et al. (2009), Yeager et al. (2011), Erens et al. (2014), MacInnis et al. (2018) and Cornesse et al. (2020) would be replicated in Australia.
Paul John Lavrakas +3 more
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