Timeline for Minimum cluster size requirements? Minimum sample size requirements for clustered standard errors?
Current License: CC BY-SA 3.0
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| Oct 4, 2011 at 20:44 | comment | added | StasK | Using t-distribution rather than z-distribution is rooted in a common (and not unreasonable) belief that t-distributions work better with finite samples. I have seen examples in survey statistics where in inference for the mean problem, you can arrive at t-distribution with clustered standard errors exactly. (You probably need balanced cluster sizes both in the sample and in the population, and equal variances across clusters, but don't quote me on that.) As for the tests, see my update on presentation materials where the test is discussed. Try searching for it on RePEc to see if it came out. | |
| Oct 4, 2011 at 20:41 | history | edited | StasK | CC BY-SA 3.0 |
added reference to Nichols and Schaffer (2007)
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| Oct 4, 2011 at 18:59 | comment | added | Chris | StasK, thank you for the answer and the references. I have another question, related to this one, but also to the answer you gave on August 10 to the question "When to use Student's or Normal distribution in linear regression?". There you imply that in the presence of clustered standard errors, one should use the normal, rather than the t-distribution for testing hypotheses about population parameters. Why then do software packages report "t-values" and probabilities in the output of regressions with cluster option? And one more question: can you test that a cluster-effect is not present? | |
| Oct 4, 2011 at 18:20 | history | answered | StasK | CC BY-SA 3.0 |