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Re: st: Test diff in R^2 from metareg models

From   Roger Harbord <>
Subject   Re: st: Test diff in R^2 from metareg models
Date   Mon, 15 Aug 2005 20:35:12 +0100

Good question Wendy, and excellent timing! Afraid I don't have a good answer at the moment, but try me again in a couple of weeks and i might well do. I'm going to a meeting about meta-analysis software next week (i think someone you know may be there too..) and one of the topics will be meta-regression. I've been thinking a bit about ANOVA-type output for meta-regression and your question is clearly related. If I remember i'll report back to the list. If i don't please remind me off-list.

My feeling is you ought to be able to do this using by computing change in a "residual" Q statistic and referring it to a chi-squared distribution, but i don't myself think meta-regression programs (including -metareg- in Stata at the moment unfortunately) calculate the Q the right way for this purpose for random-effects models at present.

One thing you could do at present though is use -test- (or -testparm-) after -metareg- to give a Wald test of the block of variables added. Will give an F-test unless you use the 'z' option to -metareg-, in which case you'll get a chi-squared test. At present I think i'd go for the F-test, but i may have changed my mind in two weeks...

At some point i plan to add a 'block' suboption to the 'permute' option in -metareg-, which would arguably be the best way to do this.

Best wishes,

--On 15 August 2005 10:21 -0500 "Garrard, Wendy M." <wendy.garrard@Vanderbilt.Edu> wrote:

I have a series of three meta-regressions, where blocks of variables
were added, resulting in an initial R^2 of 27%, the second block adding
13% to R^2, and the third block adding 25% to R^2. This is a weighted
regression with random effects (i.e., metareg).

I want to report whether the change in R^2 is significant for blocks two
and three, but am uncertain how to obtain a test (F- or Chi-sq?) of R^2
change in Stata, especially since it for metareg with random effects.

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