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Activity Number: 638 - Bayesian Methods for Time-To-Event and Frailty
Type: Contributed
Date/Time: Thursday, August 2, 2018 : 8:30 AM to 10:20 AM
Sponsor: Section on Bayesian Statistical Science
Abstract #329255 Presentation
Title: Frailty Model for Time-To-Event Data on a Social Network
Author(s): Fangda Song* and Jing Chu and Yingying Wei
Companies: The Chinese University of Hong Kong and University of Michigan and The Chinese University of Hong Kong
Keywords: social network; survival analysis; frailty model; variational EM algorithm; semi-parametric model

Nowadays, many social networks can record time-to-event data for a pair of nodes. However, despite the large body of literature on social network analysis, statistical methods for analyzing time-to-event data on social networks are still lacking. On the one hand, the pairs having time-to-event data are usually sparse on the whole network. On the other hand, the pairs with recorded data also have very small sample sizes. To allow efficient pair-specific inference, here we propose a semi-parametric frailty model with the network structure to borrow strengths. We adopt the Variational Expectation-Maximization (EM) method for fast computation and apply the proposed method to a corporate email dataset.

Authors who are presenting talks have a * after their name.

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