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Analytic Methods for Network Data

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Abstract:
This dissertation presents methods for statistical analysis of social network data. First, we develop a Bayesian hierarchical model that calibrates self and peer-reports in order to synthesize information collected from multiple sources in the social network context. Secondly we demonstrate how current methods for analyzing fixed choice design social network data can induce biases. We propose a new survey design which collects information on the total number of relationships. Lastly, we investigate how assumptions in prevalence estimation in network sampling designs can produce biased estimates and introduce a new prevalence estimator for network sampling studies that offers considerable improvement over existing estimators.
Notes:
Thesis (Ph.D. -- Brown University (2014)

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Citation

Ott, Miles Q., "Analytic Methods for Network Data" (2014). Biostatistics Theses and Dissertations. Brown Digital Repository. Brown University Library. https://doi.org/10.7301/Z0NZ8604

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