Hi, I am trying to figure out exactly what the bootcov() function in the Design package is doing within the context of clustered data. From reading the documentation/source code it appears that using bootcov() with the cluster argument constructs standard errors by resampling whole clusters of observations with replacement rather than resampling individual observations. Is that right, and is there any more detailed documentation on the math behind this? Also, what is the difference between these two functions:
bootcov(my.model, cluster.id) robcov(my.model, cluster.id) Thank you. -- View this message in context: http://www.nabble.com/Clustered-data-with-Design-package--bootcov%28%29-vs.-robcov%28%29-tp23016400p23016400.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
