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
doaj +2 more sources
Weight smoothing for nonprobability surveys [PDF]
AbstractAdjustment techniques to mitigate selection bias in nonprobability samples often involve modelling the propensity to participate in the nonprobability sample along with inverse propensity weighting. It is well known that procedures for estimating weights are effective if the covariates selected in the propensity model are related to both the ...
Ramón Ferri-García +4 more
openaire +5 more sources
Evaluating the accuracy of survey data: a case study of COVID-19 vaccination rates in Germany [PDF]
Background Surveys are an important source of timely and comprehensive population health data and play a crucial role in public health research and policymaking, as shown during the COVID-19 pandemic.
Karolina von Glasenapp
doaj +2 more sources
Nonprobability Web Surveys to Measure Sexual Behaviors and Attitudes in the General Population: A Comparison With a Probability Sample Interview Survey [PDF]
BackgroundNonprobability Web surveys using volunteer panels can provide a relatively cheap and quick alternative to traditional health and epidemiological surveys.
Erens, Bob +14 more
doaj +4 more sources
A Review of Conceptual Approaches and Empirical Evidence on Probability and Nonprobability Sample Survey Research [PDF]
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 ...
Cornesse, Carina +11 more
openaire +6 more sources
Abstract Survey researchers today can choose between relatively higher-cost probability sample telephone surveys and lower-cost surveys of nonprobability samples of potential respondents who complete questionnaires via the internet. Previous studies generally indicated that the former yield more accurate distributions of variables, but ...
Jon A Krosnick, Josh Pasek
openaire +3 more sources
Estimating response propensities in nonprobability surveys using machine learning weighted models
Propensity Score Adjustment (PSA) is a widely accepted method to reduce selection bias in nonprobability samples. In this approach, the (unknown) response probability of each individual is estimated in a nonprobability sample, using a reference probability sample.
Ramón Ferri-García +3 more
openaire +7 more sources
Theory and Practice in Nonprobability Surveys [PDF]
Andrew W. Mercer +3 more
openaire +3 more sources
Prevalence of hypertension and associated factors among sanitation workers: a community based cross-sectional survey in five urban regions of Nepal [PDF]
Background Sanitation workers represent a marginalized occupational group in Nepal often exposed to unsafe working conditions, physically demanding tasks, and occupational hazards.
Samip Khatri +7 more
doaj +2 more sources
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 ...
Wiśniowski, Arkadiusz +3 more
openaire +2 more sources

