Inference for Nonprobability Samples

Volume: 32, Issue: 2
Published: May 1, 2017
Abstract
Although selecting a probability sample has been the standard for decades when making inferences from a sample to a finite population, incentives are increasing to use nonprobability samples. In a world of “big data”, large amounts of data are available that are faster and easier to collect than are probability samples. Design-based inference, in which the distribution for inference is generated by the random mechanism used by the sampler,...
Paper Details
Title
Inference for Nonprobability Samples
Published Date
May 1, 2017
Volume
32
Issue
2
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