Analysis of Cluster-Randomized Experiments: A Comparison of Alternative Estimation Approaches
By Donald P. Green, Lynn Vavreck. Political Analysis, 2007
129 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/ea260b2cc05cd39df0cec54c869ebd256890db07
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Kevin Arceneaux
- Nathaniel P. Graham
- Susanne Köll
- Achim Zeileis
- J. Middleton
- E. Paluck
- P. M. Aronow
- David W. Nickerson
In Statistics and Probability
- Nathaniel P. Graham
- Susanne Köll
- J. Middleton
- P. M. Aronow
- Achim Zeileis
- Kevin Arceneaux
- E. Paluck
- David W. Nickerson
Citations in the corpus
- The Promising Integration of Qualitative Methods and Field Experiments (2010, background): “…Gerber 2008; Nickerson 2008; Wanketchon 2003), police raids and crime deterrence (Sherman et al. 2002), mass media programming (Paluck forthcoming; Green and Vavreck 2008), ethnic diversity (Habyarimana et al. 2007; Posner 2004), international election monitoring (Hyde 2007), deliberative…”
- Modeling Certainty with Clustered Data: A Comparison of Methods (2009, background): “In doing so,we provide analytical support for similar findings discovered by researchers using simulations (Zorn 2006; Green and Vavreck 2008).”
- A Class of Unbiased Estimators of the Average Treatment Effect in Randomized Experiments (2013, background): “Contrary to much conventional wisdom (Angrist and Lavy, 2002; Green and Vavreck, 2008; Arceneaux and Nickerson, 2009), even when all units have the same probability of entering treatment, the difference-in-means estimator is biased when clustering in treatment assignment occurs (Middleton, 2008; Mid”
- Unbiased Estimation of the Average Treatment Effect in Cluster-Randomized Experiments (2015, background): “(Hansen and Bowers, 2008, also derives design-based balance tests for cluster-randomized experiments).”
- Various Versatile Variances: An Object-Oriented Implementation of Clustered Covariances in R (2020, background): “The two most important parameters to control for this are the cluster correlation ρ , obviously, and the number of clusters G as bias decreases with increasing number of clusters (Green and Vavreck 2008; Arceneaux and Nickerson 2009; Harden 2011).”