Asymptotic seed bias in respondent-driven sampling

DOI10.1214/20-EJS1698zbMath1439.62061arXiv1808.10593OpenAlexW3015665153MaRDI QIDQ2180072

Karl Rohe, Yuling Yan, Sebastien Roch, Bret Hanlon

Publication date: 13 May 2020

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1808.10593

zbMATH Keywords

limit distributionGalton-Watson processVolz-Heckathorn estimator

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Sampling theory, sample surveys (62D05) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Branching processes (Galton-Watson, birth-and-death, etc.) (60J80) Functional limit theorems; invariance principles (60F17)

Cites Work

• Markov chains indexed by trees
• Central limit theorems for network driven sampling
• A critical threshold for design effects in network sampling
• Probability
• Generalized least squares can overcome the critical threshold in respondent-driven sampling
• Additional Limit Theorems for Indecomposable Multidimensional Galton-Watson Processes
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