Online estimation of individual-level effects using streaming shrinkage factors

Ippel, Lianne; Kaptein, Maurits; Vermunt, Jeroen K.

doi:10.1016/j.csda.2019.01.010

Computational Statistics & Data Analysis

2019

DOI: 10.1016/j.csda.2019.01.010

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Online estimation of individual-level effects using streaming shrinkage factors

Lianne Ippel

Maurits Kaptein

Jeroen K. Vermunt

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2024

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Fast meta-analytic approximations for relational event models: applications to data streams and multilevel data

Vieira,

Leenders,

Mulder

2024

J Comput Soc Sc

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Large relational-event history data stemming from large networks are becoming increasingly available due to recent technological developments (e.g. digital communication, online databases, etc). This opens many new doors to learn about complex interaction behavior between actors in temporal social networks. The relational event model has become the gold standard for relational event history analysis. Currently, however, the main bottleneck to fit relational events models is of computational nature in the form of memory storage limitations and computational complexity. Relational event models are therefore mainly used for relatively small data sets while larger, more interesting datasets, including multilevel data structures and relational event data streams, cannot be analyzed on standard desktop computers. This paper addresses this problem by developing approximation algorithms based on meta-analysis methods that can fit relational event models significantly faster while avoiding the computational issues. In particular, meta-analytic approximations are proposed for analyzing streams of relational event data, multilevel relational event data and potentially combinations thereof. The accuracy and the statistical properties of the methods are assessed using numerical simulations. Furthermore, real-world data are used to illustrate the potential of the methodology to study social interaction behavior in an organizational network and interaction behavior among political actors. The algorithms are implemented in the publicly available R package ’remx’.

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Fast meta-analytic approximations for relational event models: applications to data streams and multilevel data

Vieira,

Leenders,

Mulder

2024

J Comput Soc Sc

View full text Add to dashboard Cite

show abstract

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Online estimation of individual-level effects using streaming shrinkage factors

Cited by 1 publication

References 41 publications

Fast meta-analytic approximations for relational event models: applications to data streams and multilevel data

Fast meta-analytic approximations for relational event models: applications to data streams and multilevel data

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