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Re: st: Comparing coefficients across sub-samples


From   "Fitzgerald, James" <[email protected]>
To   "<[email protected]>" <[email protected]>
Subject   Re: st: Comparing coefficients across sub-samples
Date   Wed, 1 Aug 2012 09:04:19 +0000

Thanks again Lisa. 

On 1 Aug 2012, at 09:30, "Lisa Marie Yarnell" <[email protected]> wrote:

> Here are the full references, of the two that I had mentioned, that name effect sizes for standardized regression coefficients (standardized betas):
> Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.
> Keith, T.Z. (2006). Multiple regression and beyond. Boston: Allyn and Bacon. 
>  
> James, I don't know whether Stata can do the z-score calculation for comparing two unstandardized betas for you, but I've never had trouble doing simple calculations like this by hand.
>  
> Also, I am not sure whether all of the subscripts and superscripts came out alright for the z-score formula below, but in the denominator, the standard errors for b1 and b2 are squared.  This should also be in the Keith (2006) book, both in the text and probably on the back cover as well, where he has a lot of equations that are useful in the context of regression.
>  
>             (b1 – b2)                       b1 and b2 are the unstandardized regression weights that you want
> z = --------------------                                    to test the difference between
>       √(seb12 + seb22)                   seb1 and seb2are the standard errors of these unstandardized
>       ↑                                                    regression weights, found next to the weights themselves
>  
> Best,
> Lisa
> 
> 
> 
> ----- Original Message -----
> From: Clive Nicholas <[email protected]>
> To: [email protected]
> Cc: 
> Sent: Tuesday, July 31, 2012 9:43 PM
> Subject: Re: st: Comparing coefficients across sub-samples
> 
> Lisa Marie Yarnell replied to James Fitzgerald:
> 
> [...]
> 
>> Here are rules that I have:
>> Standardized regression coefficients:
>> * Keith’s (2006) rules for effects on school learning: .05 = too small to be considered meaningful, .above .05 = small but meaningful effect, .10 = moderate effect, .25 = large effect.
>> * Cohen’s (1988) rules of thumb: .10 = small, .30 = medium, >  (or equal to) .50 = large
> 
> Full references please, as per Statalist FAQ. I'm certainly not about
> to bust my unmentionables finding out what they are.
> 
> -- 
> Clive Nicholas
> 
> [Please DO NOT mail me personally here, but at
> <[email protected]>. Please respond to contributions I make in
> a list thread here. Thanks!]
> 
> "My colleagues in the social sciences talk a great deal about
> methodology. I prefer to call it style." -- Freeman J. Dyson
> 
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