Re: st: whether difference is significant

[Richard Goldstein <richgold@ix.netcom.com>]

you are not really supplying enough information (e.g., why 2 models?);
it appears that there are two ways to go

1. generalize Maarten's answer below and include several interactions

2. use -suest-

rich

On 10/15/12 8:13 AM, Lynn Lee wrote:
> Dear all,
> 
> I forgot to mention one point in my previous email. If I want to test the
> difference in two coefficients, I can do F test. But I do not know how to do
> it in Stata11. I want to test for several groups of coefficients. So, I need
> several independent reports of F-test. 
> 
> Any suggestion is appreciated.
> 
> Best Regards,
> Lynn Lee
> 
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Lynn Lee
> Sent: Monday, October 15, 2012 8:00 PM
> To: statalist@hsphsun2.harvard.edu
> Subject: st: whether difference is significant
> 
> I appreciate for your help, Maarten. Thank you.
> 
> Best Regards,
> Lynn Lee
> 
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Maarten Buis
> Sent: Monday, October 15, 2012 5:31 PM
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: whether difference is significant
> 
> On Mon, Oct 15, 2012 at 10:59 AM, Lynn Lee wrote:
>> I have two models:
>>
>> Y1=beta1*x1+beta2*x2+beta3*x3+u1
>> Y2=alpha1*x1+alpha2*x2+alpha3*x3+u2
>> I want to interpret whether the difference between beta1 and alpha1 is 
>> significant. How to interpret and test this significance? How to get 
>> the standard error for this difference?
> 
> That depends. In most cases where people ask this question they actually
> have one model instead of two, and the problem is solved by just adding the
> appropriate interaction terms. For example, in the example below Y1 would be
> wage for whites and Y2 would be wage for blacks. Instead of two separate
> regression, you can estimate one
> model(*) with the appropriate interaction terms.
> Since we use a log link in this example the exponentiated coefficients are
> ratios not differences, so the effect of union for blacks is 1.25 times as
> large as the effect of union for whites (the reference) and this ratio is
> significantly different from 1(**).
> 
> *---------------- begin example ------------------ sysuse nlsw88, clear gen
> black = race ==2 if race < 3 glm wage i.black##(c.grade c.ttl_exp i.union),
> ///
>     link(log) vce(robust) eform
> *----------------- end example ------------------- (For more on examples I
> sent to the Statalist see:
> http://www.maartenbuis.nl/example_faq )
> 
> Hope this helps,
> Maarten
> 
> (*) In this case I use -glm- to model log(E(wage)) instead of E(log(wage)),
> as we are typically interested in E(wage) not E(log(wage)). See:
> <http://blog.stata.com/2011/08/22/use-poisson-rather-than-regress-tell-a-fri
> end/>.
> 
> (**) For ratios the number 1 represents "no effect"; 1 X some number = some
> number.
> 
> ---------------------------------
> Maarten L. Buis
> WZB
> Reichpietschufer 50
> 10785 Berlin
> Germany
> 
> http://www.maartenbuis.nl
> ---------------------------------
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