Journal Article

Adaptive and Network Sampling for Inference and Interventions in Changing Populations

Steven K. Thompson

in Journal of Survey Statistics and Methodology

Volume 5, issue 1, pages 1-21
Published in print March 2017 | ISSN: 2325-0984
Published online March 2017 | e-ISSN: 2325-0992 | DOI: https://dx.doi.org/10.1093/jssam/smw035
Adaptive and Network Sampling for Inference and Interventions in Changing Populations

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In this paper, I discuss some of the wider uses of adaptive and network sampling designs. Three uses of sampling designs are to select units from a population to make inferences about population values, to select units to use in an experiment, and to distribute interventions to benefit a population. The most useful approaches for inference from adaptively selected samples are design-based methods and Bayesian methods. Adaptive link-tracing network sampling methods are important for sampling populations that are otherwise hard to reach. Sampling in changing populations involves temporal network or spatial sampling design processes with units selected both into and out of the sample over time. Averaging or smoothing fast-moving versions of these designs provides simple estimates of network-related characteristics. The effectiveness of intervention programs to benefit populations depends a great deal on the sampling and assignment designs used in spreading the intervention.

Keywords: Adaptive sampling; Experiments; Inference; Interventions; Network sampling; Sampling; Temporal sampling

Journal Article.  8340 words.  Illustrated.

Subjects: Social Research and Statistics

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