Hi Laurie

LP> Thanks for your reply Martha. It's good to find out that I'm going wrong,

LP> but hard to see where. I have checked the formula using the worked examples

LP> given in Lipsey & Wilson (2001). Practical meta-analysis. Thousand Oaks:

LP> Sage and the formulae give the correct results based on their data.... I've

LP> just tried a different way:

LP> =AN2*((AL2-$AO$47)^2)

Yes, this is the formula.

LP> where AN2 is the weighted inverse varience weight for the effects size in

LP> question, AL2 is the unbiassed effects size in question and $AO$47 is the

LP> weighted mean effects size. I have then summed these figures to give a Q of

LP> 88.84. This is well above the p=0.05 critical value of 55.76, which is

LP> given in my chi squared distribution table for df=40, the closest I have to

LP> my df (41).

If you are using Excel, then you can get the p-value for your Q

statistic using one of the statistical functions imbedded in the

program: in English is CHIDIST, in French LOY.KHIDEUX (I've always

found surprising the fact that Excel functions have different names

according to the language...)

LP> I'll try the code you wrote. If you could send the macros, that

LP> would be a huge help.

Are you doing meta-analysis of countinuous or binary outcomes? (just

to know which one to send).

--

Regards,

Dr. Marta García-Granero,PhD mailto:

[hidden email]
Statistician

---

"It is unwise to use a statistical procedure whose use one does

not understand. SPSS syntax guide cannot supply this knowledge, and it

is certainly no substitute for the basic understanding of statistics

and statistical thinking that is essential for the wise choice of

methods and the correct interpretation of their results".

(Adapted from WinPepi manual - I'm sure Joe Abrahmson will not mind)