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EDO AIROLDI - Harvard University

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'Valid inference from non-ignorable network sampling designs'
14 March 2013 from 4:00 PM to 5:00 PM
201 Thomas Bldg.
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A number of scientific endeavors of current national and international interest involve populations with interacting and/or interfering units. In these problems, a collection of partial measurements about patterns of interaction and interference (e.g., social structure and familial relations) is available, in addition to the more traditional measurements about unit-level outcomes and covariates. Formal statistical models for the analysis of this type of data have emerged as a major topic of interest in diverse areas of study. In this talk, I will review a few ideas and open areas of research that are central to this burgeoning literature, placing emphasis on inference and other core statistical issues. Then I will turn to describe a new notion of non-ignorability that applies to network sampling designs, and an inference strategy that can be used to obtain valid estimates in these settings, with hints to the applications in marketing on social media platforms and healthcare in which these statistical problems arise.

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