[posted and mailed] Rich Ulrich <[EMAIL PROTECTED]> wrote in <[EMAIL PROTECTED]>: > > >On Wed, 16 May 2001 11:50:07 +0000 (UTC), [EMAIL PROTECTED] >(rpking) wrote: > >> For each of the two variance ratios, A=var(x)/var(y) and >> B=var(w)/var(z), I bootstrapped with 2000 replications to obtain >> confidence intervals. Now I want to test whether the means are >> equal, ie. E(A) = E(B), >Why do you want ratios of the variances? If you are concerned with >variances, why aren't you considering the logs of V? If you are >concerned with ratios, why are you considering the logs of the ratios? I want ratios of variances because I want to test an economic theory which is based on ratios of variances. It's the production smoothing hypothesis of inventory theory; simply put, the variance of production should be less than the variance of sales. The variance ratio is a standard metric used in the literature. >Bootstrapping is tough enough to figure what's proper, that I >don't want to bother with it. Direct tests are usually enough: So, >if you were considering a direct test, What would you be testing? >(I figure there is really good chance that you are wrong in what you >are trying to bootstrap, or how you are doing it.) I use bootstrap to get the confidence intervals for A and B because they are both >0 by construction, so the exact distributions of A and B cannot be normal, and thus starndard distribution theory cannot be used to obtain CIs. Now I want to test the null hypothesis that A - B=0. Let D=A-B. Could D have a normal distribution? I don't know, and that's why I'm asking. > ... and that is relevant to what? Distributions of raw data are >seldom (if ever) "asymptotically normal". So no social scientist should ever use asymptotic theory in their anaysis of (raw) data? This is certainly a very extreme view. Still welcome suggestions! ================================================================= Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =================================================================
