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I have three sets of data sets each 10 to 20 data points. I want to test if the coefficient of variation is the same across all the sets. Please suggest relevant methods.

I came across papers by Cabras(2006) and Amiri(2010). One, they look at comparing only two samples and two, my knowledge of simulation / econometric methods is elementary. Are there packages in [R] or Stata that are available to do this?

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There is an R package on CRAN for the Feltz and Miller Asymptotic Test: cvequality

That package also has a function for the ‘Modified signed-likelihood ratio test (SLRT) for equality of CVs’ (Krishnamoorthy and Lee 2014).

And it has a very nice vignette showing how to use the functions ;) (disclaimer: I'm the package author)

References:

Feltz, C. J., & Miller, G. E. (1996). An asymptotic test for the equality of coefficients of variation from k populations. Statistics in Medicine, 15(6), 647-658. https://www.ncbi.nlm.nih.gov/pubmed/8731006

Krishnamoorthy, K., & Lee, M. (2014). Improved tests for the equality of normal coefficients of variation. Computational Statistics, 29(1-2), 215-232. http://link.springer.com/article/10.1007/s00180-013-0445-2

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  • $\begingroup$ Thanks, These tests confirm if the COV are different. If I want to test for $\endgroup$ – Piyush Shah Dec 30 '16 at 16:00
  • $\begingroup$ Thanks, These tests confirm if the COV are different. If I want to test for CV1 > CV2 > CV3, do we have some version of post hoc tests? Or can I look at the values of CV of the samples and directly infer? $\endgroup$ – Piyush Shah Dec 30 '16 at 16:05
  • $\begingroup$ You're welcome! I'm not currently aware of a post-hoc test. I'd suggest simply plotting the distributions to infer directly, as you can see in the vignette of the cvequality package $\endgroup$ – Ben Dec 31 '16 at 10:16

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