Results 21 to 30 of about 1,222,703 (195)
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; id_orcid 0000-0002-7567-3600 +3 more
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Workplace Policy Awareness, Training, and Supervisory Support as Correlates of Generative Artificial Intelligence Use Among Practicing Nurses. [PDF]
Nurs OpenABSTRACT Aim To estimate the prevalence and frequency of generative artificial intelligence (AI) use among practicing nurses and to determine whether four workplace governance conditions were independently associated with use. Design US‐wide nonprobability cross‐sectional survey.
Carter GA.
europepmc +2 more sources
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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A Demonstration of Propensity-Score Weighting to Adjust a Social Media Nonprobability Sample Survey of Political Attitudes. [PDF]
Public Opin QAbstract Interest in using nonprobability online samples continues to grow despite concerns about selection bias. Many methods exist for adjusting nonprobability data so it may yield generalizable inferences. Here we investigate whether a propensity score weighting method can balance differences between a probability sample and a ...
Pollard MS, Robbins MW, Griswold M.
europepmc +3 more sources
Blending Probability and Nonprobability Samples with Applications to a Survey of Military Caregivers [PDF]
Journal of Survey Statistics and Methodology, 2020 AbstractProbability samples are the preferred method for providing inferences that are generalizable to a larger population. However, in many cases, this approach is unlikely to yield a sample size large enough to produce precise inferences. Our goal here is to improve the efficiency of inferences from a probability sample by combining (or blending) it
Michael W Robbins +2 more
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Recent Advances in Probability-Based and Nonprobability Survey Research
Journal of Survey Statistics and Methodology, 2020 At the turn of the decade, this special issue is a symbol of transformation in the survey world that slowly started in the 2000s and that is likely to continue into the future. At the heart of this transformation lies an age-old academic debate on the merits and costs of probability sampling methods for survey research.
Blom, Annelies G. +3 more
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Weighting Nonprobability and Probability Sample Surveys in Describing Cancer Catchment Areas [PDF]
Cancer Epidemiology, Biomarkers & Prevention, 2019 Abstract Background: The Population Health Assessment initiative by NCI sought to enhance cancer centers’ capacity to acquire, aggregate, and integrate data from multiple sources, as well as to plan, coordinate, and enhance catchment area analysis activities.
Ronaldo Iachan +7 more
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JMIR Research Protocols, 2022 BackgroundEpidemiologic research among migrant populations is limited by logistical, methodological, and ethical challenges, but it is necessary for informing public health and humanitarian programming.
Andrea L Wirtz +14 more
doaj +1 more source
Fraud in Online Surveys: Evidence from a Nonprobability, Subpopulation Sample
Journal of Experimental Political Science, 2022 We 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 survey
Andrew M. Bell, Thomas Gift
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JMIR Research Protocols, 2023 BackgroundRespondent-driven sampling (RDS) is a nonprobability sampling technique that allows the extrapolation of its outcome to the target population.
Mihir Bhatta +5 more
doaj +1 more source