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2016
A sample is a subset of a population and we survey the units from the sample with the aim to learn about the entire population. However, the sampling theory was basically developed for probability sampling, where all units in the population have known and positive probabilities of inclusion. This definition implicitly involves randomization, which is a
Vehovar, V., Toepoel, V., Steinmetz, S.
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A sample is a subset of a population and we survey the units from the sample with the aim to learn about the entire population. However, the sampling theory was basically developed for probability sampling, where all units in the population have known and positive probabilities of inclusion. This definition implicitly involves randomization, which is a
Vehovar, V., Toepoel, V., Steinmetz, S.
openaire +5 more sources
Sampling: bridging probability and non-probability designs
International Journal of Social Research Methodology, 2013This article reconceptualizes sampling in social research. It is argued that three inter-related a priori assumptions limit on the possibility of sample design, namely: (a) the ontology of the case, (b) the epistemological assumptions underpinning what properties are necessary to know the case and (c) the logistics involved in the process of ‘casing ...
E. Uprichard
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Transgender Health, 2022
Non-probability sampling methods utilize nonrandom research participant selection, which may generate study samples that are not representative of the general population.
J. Turban +3 more
semanticscholar +1 more source
Non-probability sampling methods utilize nonrandom research participant selection, which may generate study samples that are not representative of the general population.
J. Turban +3 more
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Comparing Inference Methods for Non‐probability Samples
International Statistical Review, 2018SummarySocial and economic scientists are tempted to use emerging data sources like big data to compile information about finite populations as an alternative for traditional survey samples. These data sources generally cover an unknown part of the population of interest.
Bart Buelens +2 more
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Model-assisted SCAD calibration for non-probability samples
Brazilian Journal of Probability and Statistics, 2021zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Liu, Zhan, Tu, Chaofeng, Pan, Yingli
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Non-probability Survey Samples
2020We provide an overview of the emerging topic of non-probability survey samples which has drawn increased attention in the fields of survey methodology and official statistics. We highlight some of the issues in analyzing non-probability survey samples and present some of the methodological advances that have appeared in recent years.
Changbao Wu, Mary E. Thompson
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Journal of Official Statistics
In this article, the estimators based on data from independent non-probability and probability samples are combined to estimate finite population parameters. Assuming that the values of the study variable are available in both samples, the integration of
Andrius Čiginas +2 more
semanticscholar +1 more source
In this article, the estimators based on data from independent non-probability and probability samples are combined to estimate finite population parameters. Assuming that the values of the study variable are available in both samples, the integration of
Andrius Čiginas +2 more
semanticscholar +1 more source
Tracing Selection Effects in Three Non-Probability Samples
European Addiction Research, 2005Snowball sampling and targeted sampling are widely applied techniques to recruit samples from hidden populations, such as problematic drug users. The disadvantage is that they yield non-probability samples which cannot be generalised to the population. Despite thorough preparatory mapping procedures, selection effects continue to occur.
Cas, Barendregt +2 more
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