Abstract
Temporal network data is often encoded as time-stamped interaction events between senders and receivers, such as co-authoring scientific articles or communication via email. A number of relational event frameworks have been proposed to address specific issues raised by complex temporal dependencies. These models attempt to quantify how individual behaviour, endogenous and exogenous factors, as well as interactions with other individuals modify the network dynamics over time. It is often of interest to determine whether changes in the network can be attributed to endogenous mechanisms reflecting natural relational tendencies, such as reciprocity or triadic effects. The propensity to form or receive ties can also, at least partially, be related to actor attributes. Nodal heterogeneity in the network is often modelled by including actor-specific or dyadic covariates. However, comprehensively capturing all personality traits is difficult in practice, if not impossible. A failure to account for heterogeneity may confound the substantive effect of key variables of interest. This work shows that failing to account for node level sender and receiver effects can induce ghost triadic effects. We propose a random-effect extension of the relational event model to deal with these problems. We show that it is often effective over more traditional approaches, such as in-degree and out-degree statistics. These results that the violation of the hierarchy principle due to insufficient information about nodal heterogeneity can be resolved by including random effects in the relational event model as a standard.
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Acknowledgements
This work was supported by an STSM Grant from COST Action COSTNET (CA15109). EW acknowledges funding by SNSF (Grants 188534, 192549).
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Appendices
Social evolution study: model output
The final random effects model selected also included two fixed effects, namely whether they lived on the same floor and whether they were in the same year. Both effects are positive, suggesting that sharing floor and year increases the rate of interaction.
Classroom study: model output
The final random effects model selected also included three fixed effects, namely whether the receiver is female, whether the sender is a teacher and whether the receiver is a teacher. The first effect is not significant, whereas teachers have higher sending propensity and a lower receiving propensity, compared to students.
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Juozaitienė, R., Wit, E.C. Nodal Heterogeneity can Induce Ghost Triadic Effects in Relational Event Models. Psychometrika (2024). https://doi.org/10.1007/s11336-024-09952-x
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DOI: https://doi.org/10.1007/s11336-024-09952-x