Dear John,
Thanks for this, the gfields is indeed very useful! I am now using it and it gives me pretty nice results. However I am surprised that the contribution of one of my explanatory variables is negative (although small). Any idea why this can be the case?
Many thanks, Alice.
--- On Fri, 28/11/08, John Antonakis <[email protected]> wrote:
> From: John Antonakis <[email protected]>
> Subject: Re: st: Anova
> To: [email protected]
> Date: Friday, 28 November, 2008, 4:32 PM
> Simply estimate:
>
> xi: reg y x1 x2 x3 x4 x4 x6 i.dumm, beta.
>
> If your variables are either binary or continuous variables
> then you can examine the beta coefficient (i.e.,
> standardized) for relative impact.
>
> For other ways to look at coefficients download
> "listcoef".
>
> Also "gfields" is nice for breaking down
> variance.
>
> If you have categorical data with more than two categories
> use the "test" command to test whether the dummies
> of that variable dummies are jointly different from zero:
> e.g., test I_dumm1 I_dumm2
>
> I guess you could convert that F or chi-square that it
> reports to an effect size.
>
> HTH,
> John Antonakis
> University of Lausanne
> Switzerland
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