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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp014m90dx89q
 Title: Network Reporting Methods Authors: Feehan, Dennis Michael Advisors: Salganik, Matthew J. Contributors: Population Studies Department Keywords: demographyHIVmortalitysamplingsocial networksstatistics Subjects: DemographyStatisticsSociology Issue Date: 2015 Publisher: Princeton, NJ : Princeton University Abstract: This dissertation is about how the science of sampling and survey research can be generalized beyond the individual: while traditional surveys ask respondents to report about themselves, we study network reporting surveys in which respondents are asked to report about others. Despite many technical challenges, understanding how to design and analyze network reporting studies is worth the effort: network reporting surveys can be used to study many important rare and hidden populations for which traditional survey methods are inadequate. We begin by introducing the network reporting framework, a general toolkit that can help researchers develop new estimators and new data collection methods. The framework can also help researchers better understand many existing estimators. We apply the framework to analyze network scale-up, an existing method for studying epidemiologically important hidden populations like sex workers and drug injectors. We derive the precise conditions required for the basic scale-up estimator to have desirable statistical properties; we also introduce a new, generalized scale-up estimator, which we expect to outperform the existing estimator in many settings. Next, we turn to a key question for all network reporting studies: which personal network should respondents be asked to report about? We conjecture that there may be a trade-off between the quantity and the quality of information obtained from different personal networks. We test this conjecture by embedding an experiment in a large, nationally-representative household survey that we conducted in Rwanda. Our results show that there may indeed be a trade-off, but future work is required to understand this possibility in more detail. Finally, we apply the network reporting framework to a critical, unsolved problem in demography: estimating adult death rates in countries that lack complete vital registration systems. We introduce a new estimator and data collection procedure called network survival, and we test our new approach using the Rwanda survey. Our results demonstrate that a network reporting study is feasible in an environment where adult mortality estimates are sorely needed, and the estimated network survival rates have plausible levels and age-patterns. However, more work is required before we can fully assess the accuracy of this new approach. URI: http://arks.princeton.edu/ark:/88435/dsp014m90dx89q Alternate format: The Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the library's main catalog: http://catalog.princeton.edu/ Type of Material: Academic dissertations (Ph.D.) Language: en Appears in Collections: Population Studies

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