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From |
David Radwin <[email protected]> |

To |
[email protected] |

Subject |
Re: st: Alternative to coefficient of variation (CV)/relative standard error as a measure of estimate's reliability/stability |

Date |
Tue, 12 Jun 2012 22:42:52 -0700 (PDT) |

Nick, Thank you for your thoughtful contribution. I personally agree with your criticism of a one-size-fits-all solution, but that is the sort of statistic I am seeking nonetheless. I would very much appreciate suggestions, however imperfect they may be, from other Statalisters. Incidentally, an even more thorny situation is when the estimate is zero or close to zero, perhaps because it has been mean-deviated (demeaned) or is a measure of change when there is no change. Then the CV is undefined or essentially infinity! David -- David Radwin Senior Research Associate MPR Associates, Inc. 2150 Shattuck Ave., Suite 800 Berkeley, CA 94704 Phone: 510-849-4942 Fax: 510-849-0794 www.mprinc.com ----- Original Message ----- From: "Nick Cox" <[email protected]> To: [email protected] Sent: Tuesday, June 12, 2012 5:57:44 PM Subject: Re: st: Alternative to coefficient of variation (CV)/relative standard error as a measure of estimate's reliability/stability A simple-minded but I think reasonable first stab at this issue is that the CV is a fair criterion if SD (specifically SE) is indeed proportional to mean (generally estimate), so that SD / mean is approximately constant in a given kind of situation. If that is not true as a kind of first approximation then information is needed on the relation between variability and estimate to make a better judgement. One example that I studied in excruciating detail several years ago was the variability of annual rainfall in which many people had been led from the observation that variability of rainfall as measured by SD tends to increase with the mean to conclude that the CV was in some sense a better summary. However, in many cases it is more nearly true that SD varies as a power around 0.7 of the mean, in which case CV over-compensates. CV is, as you imply, even less appropriate for proportions. I'm not sure this will help you at all. I became sensitive to inappropriate uses of the CV years ago when I encountered examples even worse than those with annual rainfall and my best summary is that when the CV is not appropriate there is not usually a simpler or even different alternative that works well at all; rather analysis has to look directly at the structure of variability. Nick On Wed, Jun 13, 2012 at 12:37 AM, David Radwin <[email protected]> wrote: > I hope you will indulge me this statistics question that is not strictly > Stata-specific. I am looking for a statistic measuring an estimate's > reliability or stability as an alternative to the coefficient of variation > (CV), also known as the relative standard error. The CV is the standard > error of an estimate (proportion, mean, regression coefficient, etc.) > divided by the estimate itself, usually expressed as a percentage. For > example, if a survey finds 15% unemployment with a 6% standard error, the > CV is .06/.15 = .4 = 40%. > > Some US government agencies flag or suppress as unreliable any estimate > with a CV over a certain threshold such as 30% or 50%. But this standard > can be arbitrary (for example, 85% employment would have a much lower CV > of .06/.85 = 7%) and has other limitations. > > Can anyone suggest an alternative measure of stability or reliability? * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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