Vu, Duy, Lomi, Alessandro, Mascia, Daniele and Pallotti, Francesca (2017) Relational event models for longitudinal network data with an application to interhospital patient transfers. Statistics in Medicine, 36 (14). pp. 2265-2287. ISSN 0277-6715 (Print), 1097-0258 (Online) (doi:10.1002/sim.7247)

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Abstract

The main objective of this paper is to introduce and illustrate relational event models, a new class of statistical models for the analysis of time-stamped data with complex temporal and relational dependencies. We outline the main differences between recently proposed relational event models and more conventional network models based on the graph-theoretic formalism typically adopted in empirical studies of social networks. Our main contribution involves the definition and implementation of a marked point process extension of currently available models. According to this approach, the sequence of events of interest is decomposed into two components: (a) event time, and (b) event destination. This decomposition transforms the problem of selection of event destination in relational event models into a conditional multinomial logistic regression problem. The main advantages of this formulation are the possibility of controlling for the effect of event-specific data and a significant reduction in the estimation time of currently available relational event models. We demonstrate the empirical value of the model in an analysis of interhospital patient transfer within a regional community of health care organizations. We conclude with a discussion of how the models we presented help to overcome some the limitations of statistical models for networks that are currently available.

Item Type:	Article
Uncontrolled Keywords:	Social network analysis; Relational event models; Inter-organizational relations, Interhospital patient transfers
Subjects:	H Social Sciences > HA Statistics
Faculty / School / Research Centre / Research Group:	Faculty of Business Faculty of Business > Networks and Urban Systems Centre (NUSC) > Centre for Business Network Analysis (CBNA) Faculty of Business > Department of International Business & Economics
Last Modified:	31 Mar 2018 00:38
URI:	http://gala.gre.ac.uk/id/eprint/16323

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