Clustered data is common in political science research.
➡️ The Problem: Standard methods can produce misleading statistics when there are few clusters (G), even if each cluster has many observations.
➡️ New Solutions: This paper provides user-friendly Stata and R packages that offer better uncertainty measures for small G.
➡️ Why It Matters: Reanalyzing recent work with the new methods shows more reliable results than relying on traditional cluster-robust standard errors.
| Practical and Effective Approaches to Dealing with Clustered Data was authored by Justin Esarey and Andrew Menger. It was published by Cambridge in PSR&M in 2019. |
