Taking dyads seriously
| Autor: | Cassy Dorff, Max Gallop, Margaret Foster, Michael D. Ward, Juan Fernando Tellez, Howard Liu, Shahryar Minhas |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
021110 strategic
defence & security studies Sociology and Political Science Process (engineering) Computer science 05 social sciences 0211 other engineering and technologies Inference 02 engineering and technology 16. Peace & justice Dyadic data Regression 0506 political science Scholarship Standard error Political Science and International Relations 050602 political science & public administration Key (cryptography) Econometrics JZ |
| ISSN: | 2049-8489 |
| Popis: | International relations scholarship concerns dyads, yet standard modeling approaches fail to adequately capture the data generating process behind dyadic events and processes. As a result, they suffer from biased coefficients and poorly calibrated standard errors. We show how a regression-based approach, the Additive and Multiplicative Effects (AME) model, can be used to account for the inherent dependencies in dyadic data and glean substantive insights in the interrelations between actors. First, we conduct a simulation to highlight how the model captures dependencies and show that accounting for these processes improves our ability to conduct inference on dyadic data. Second, we compare the AME model to approaches used in three prominent studies from recent international relations scholarship. For each study, we find that compared to AME, the modeling approach used performs notably worse at capturing the data generating process. Further, conventional methods misstate the effect of key variables and the uncertainty in these effects. Finally, AME outperforms standard approaches in terms of out-of-sample fit. In sum, our work shows the consequences of failing to take the dependencies inherent to dyadic data seriously. Most importantly, by better modeling the data generating process underlying political phenomena, the AME framework improves scholars’ ability to conduct inferential analyses on dyadic data. |
| Databáze: | OpenAIRE |
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