Skip to main content
Cross Validated

You are not logged in. Your edit will be placed in a queue until it is peer reviewed.

We welcome edits that make the post easier to understand and more valuable for readers. Because community members review edits, please try to make the post substantially better than how you found it, for example, by fixing grammar or adding additional resources and hyperlinks.

4
  • 1
    $\begingroup$ Thank you for the citation! Bradley's work seems quite old so I suspect it does not have much work on modern simulation studies to compare efficiencies and Type I/II error rates in various scenarios? I'd also be interested in what he suggests about Brunner-Munzel tests - should they be used instead of a U test if variances in the two groups are not known to be equal? $\endgroup$ Commented Nov 5, 2014 at 22:11
  • 1
    $\begingroup$ Bradley does discuss efficiencies, although most of the time, it is in the context of asymptotic relative efficiency. He brings sources sometimes for statements about finite sample-size efficiency, but as the work is from 1968, I'm sure much better analyses have been done since then. Speaking of which, If I have it right, Brunner and Munzel wrote their article in 2000, which explains why there is no mention of it in Bradley. $\endgroup$ Commented Nov 5, 2014 at 23:23
  • $\begingroup$ Yes that would indeed explain it! :) Do you know if there is a more up to date survey than Bradley? $\endgroup$ Commented Nov 5, 2014 at 23:25
  • $\begingroup$ A brief search shows that there are a lot of recent texts on non-parametric statistics. For example: Nonparametric Statistical Methods (Hollander et al, 2013), Nonparametric Hypothesis Testing: Rank and Permutation Methods with Applications in R (Bonnini et al, 2014), Nonparametric Statistical Inference, Fifth Edition (Gibbons and Chakraborti, 2010). There are many others which come up in various searches. As I don't have any, I cannot make any recommendations. Sorry. $\endgroup$ Commented Nov 6, 2014 at 0:20