Bookmark and Share

Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.


[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

RE: st: Comparing coefficients across sub-samples


From   "Fitzgerald, James" <[email protected]>
To   Lisa Marie Yarnell <[email protected]>, "[email protected]" <[email protected]>
Subject   RE: st: Comparing coefficients across sub-samples
Date   Wed, 1 Aug 2012 07:04:56 +0000

Hi Lisa

Thank you very much for your response!

I am looking for both the methodology and the command, if it exists.

Does Stata have a command for generating "standardised" betas, or do I just transform my variables by hand and re-run my regressions?

Thanks again

James

________________________________________
From: Lisa Marie Yarnell [[email protected]]
Sent: 01 August 2012 04:29
To: [email protected]; Fitzgerald, James
Subject: Re: st: Comparing coefficients across sub-samples

Hi James,

Typically the effect of a predictor in two different groups can be compared with the unstandardized beta. You can do a statistical test of the difference in the betas using the z-score formula below.  I usually just calculate the difference between unstandardized betas from two different models by hand, though Stata might have a command to do this for you.  Is that what you are looking for: the Stata command?

            (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
This is a square root sign!                      in your SPSS output.  Remember to square them.
Take the square root of the
entire value in parentheses.

In terms of comparing the *magnitude* of the effect in the two different subsamples, it is more correct to do this qualitatively by comparing the *standardized* beta for the variable of interest against effect size rules of thumb for small/medium/large (which sometimes differ by discipline, such as social sciences/education/engineering).  Just report the standardized beta as the effect size in each group; it would be a qualitative statement about the effect in each group.

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

Lisa




----- Original Message -----
From: "Fitzgerald, James" <[email protected]>
To: "[email protected]" <[email protected]>
Cc:
Sent: Tuesday, July 31, 2012 4:14 PM
Subject: st: Comparing coefficients across sub-samples

Hi Statalisters

I am running the same model on two sub-samples as follows:

xtreg ltdbv lnta tang itang prof mtb if nolowlntalowtang==1, fe cluster(firm)

xtreg ltdbv lnta tang itang prof mtb if nolowlntalowtang==0, fe cluster(firm)

I want to compare the explanatory power of lnta across the two sub-samples i.e. in which sub-sample does lnta explain significantly more of the variation in ltdbv?

Can anyone give me some advice on how to achieve this?

Thanks in advance

James
*
*  For searches and help try:
*  http://www.stata.com/help.cgi?search
*  http://www.stata.com/support/statalist/faq
*  http://www.ats.ucla.edu/stat/stata/

*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/


© Copyright 1996–2018 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   Site index