ICAR Research Data Repository for Knowledge Management
Replication data for: Understanding Interaction Models: Improving Empirical Analyses
Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)
View Archive Info| Field | Value | |
| Title |
Replication data for: Understanding Interaction Models: Improving Empirical Analyses
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| Identifier |
https://doi.org/10.7910/DVN/B8YKU3
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| Creator |
Thomas Brambor
William Clark Matt Golder |
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| Publisher |
Harvard Dataverse
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| Description |
Multiplicative interaction models are common in the quantitative political science literature. This is so for good reason. Institutional arguments frequently imply that the relationship between political inputs and outcomes varies depending on the institutional context. Models of strategic interaction typically produce conditional hypotheses as well. Although conditional hypotheses are ubiquitous in political science and multiplicative interaction models have been found to capture their intuition quite well, a survey of the top three political science journals from 1998 to 2002 suggests that the execution of these models is often flawed and inferential errors are common. We believe that considerable progress in our understanding of the political world can occur if scholars follow the simple checklist of dos and don’ts for using multiplicative interaction models presented in this article. Only 10% of the articles in our survey followed the checklist.
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| Date |
2006
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| Relation |
Thomas Brambor, William Roberts, Matt Golder. 2004. "Electoral System Choice." Unpublished replication, New York University. dataverse available here Thomas Brambor, William Roberts Clark, Matt Golder. 2004. "Gubernatorial and Presidential Coattails in Brazil." Unpublished replication, New York University. dataverse available here |
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