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'Predicting' after peeking into the future: Correcting a fundamental flaw in the SAOM -- TERGM comparison of Leifeld and Cranmer (2019)

Authors :
Block, Per
Hollway, James
Stadtfeld, Christoph
Koskinen, Johan
Snijders, Tom
Source :
Network Science, Volume 10, Issue 1, March 2022, pp. 3 - 14
Publication Year :
2019

Abstract

We review the empirical comparison of SAOMs and TERGMs by Leifeld and Cranmer (2019) in Network Science. We note that their model specification uses nodal covariates calculated from observed degrees instead of using structural effects, thus turning endogeneity into circularity. In consequence, their out-of-sample predictions using TERGMs are based on out-of-sample information and thereby predict the future using observations from the future. We conclude that their analysis rest on erroneous model specifications that render the article's conclusions meaningless. Consequently, researchers should disregard recommendations from the criticized paper when making informed modelling choices.

Subjects

Subjects :
Statistics - Methodology

Details

Database :
arXiv
Journal :
Network Science, Volume 10, Issue 1, March 2022, pp. 3 - 14
Publication Type :
Report
Accession number :
edsarx.1911.01385
Document Type :
Working Paper
Full Text :
https://doi.org/10.1017/nws.2022.6