Replication Data for: Taking Dyads Seriously
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'International relations scholarship concerns dyads, yet standardmodeling approaches fail to adequately capture the data generatingprocess behind dyadic events and processes. As a result, they sufferfrom biased coefficients and poorly calibrated standard errors. We showhow a regression-based approach, the Additive and Multiplicative Effects(AME) model, can be used to account for the inherent dependencies indyadic data and glean substantive sights in the interrelations betweenactors. First, we conduct a simulation to highlight how the modelcaptures dependencies and show that accounting for these processesimproves our ability to conduct inference on dyadic data. Second, wecompare the AME model to approaches used in three prominent studiesfrom recent international relations scholarship. For each study, we findthat compared to AME' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["bayesian","latent variable models","multi-level and hierarchical models"]} <|eot_id|>
 Here is the Description of a dataset. Description:'International relations scholarship concerns dyads, yet standardmodeling approaches fail to adequately capture the data generatingprocess behind dyadic events and processes. As a result, they sufferfrom biased coefficients and poorly calibrated standard errors. We showhow a regression-based approach, the Additive and Multiplicative Effects(AME) model, can be used to account for the inherent dependencies indyadic data and glean substantive sights in the interrelations betweenactors. First, we conduct a simulation to highlight how the modelcaptures dependencies and show that accounting for these processesimproves our ability to conduct inference on dyadic data. Second, wecompare the AME model to approaches used in three prominent studiesfrom recent international relations scholarship. For each study, we findthat compared to AME' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
International relations scholarship concerns dyads, yet standardmodeling approaches fail to adequately capture the data generatingprocess behind dyadic events and processes. As a result, they sufferfrom biased coefficients and poorly calibrated standard errors. We showhow a regression-based approach, the Additive and Multiplicative Effects(AME) model, can be used to account for the inherent dependencies indyadic data and glean substantive sights in the interrelations betweenactors. First, we conduct a simulation to highlight how the modelcaptures dependencies and show that accounting for these processesimproves our ability to conduct inference on dyadic data. Second, wecompare the AME model to approaches used in three prominent studiesfrom recent international relations scholarship. For each study, we findthat compared to AME
bayesian; latent variable models; multi-level and hierarchical models