scholarly journals Multiway Clustering for Creating Biomedical Term Sets

2008 ◽  
Author(s):  
Vasileios Kandylas ◽  
Lyle Ungar ◽  
Ted Sandler ◽  
Shane Jensen
Keyword(s):  
Multiway Clustering

scholarly journals Robust Inference With Multiway Clustering

2011 ◽  
Vol 29 (2) ◽  
pp. 238-249 ◽  
Author(s):  
A. Colin Cameron ◽  
Jonah B. Gelbach ◽  
Douglas L. Miller
Keyword(s):  
Robust Inference ◽  
Multiway Clustering

scholarly journals Wild Bootstrap and Asymptotic Inference With Multiway Clustering

2019 ◽  
pp. 1-15 ◽  
Author(s):  
James G. MacKinnon ◽  
Morten Ørregaard Nielsen ◽  
Matthew D. Webb
Keyword(s):  
Wild Bootstrap ◽  
Asymptotic Inference ◽  
Multiway Clustering

scholarly journals vcemway: A one-stop solution for robust inference with multiway clustering

2019 ◽  
Vol 19 (4) ◽  
pp. 900-912 ◽  
Author(s):  
Ariel Gu ◽  
Hong Il Yoo
Keyword(s):  
Covariance Matrix ◽  
Confidence Intervals ◽  
Robust Inference ◽  
Standard Errors ◽  
One Stop ◽  
Multiway Clustering

Most Stata commands allow cluster( varname) or vce(cluster clustvar) as an option, popularizing the use of standard errors that are robust to oneway clustering. For adjusting standard errors for multiway clustering, there is no solution that is as widely applicable. While several community-contributed packages support multiway clustering, each package is compatible only with a subset of models that Stata’s ever-expanding library of commands allows the researcher to fit. We introduce a command, vcemway, that provides a one-stop solution for multiway clustering. vcemway works with any estimation command that allows cluster( varname) as an option, and it adjusts standard errors, individual significance statistics, and confidence intervals in output tables for multiway clustering in specified dimensions. The covariance matrix used in making this adjustment is stored in e(V), meaning that any subsequent call to postestimation commands that use e(V) as input (for example, test and margins) will also produce results that are robust to multiway clustering.

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