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# RE: Wald test: alternatives and small sample sizes

 From "Collewaert V (MCFE)" To "statalist@hsphsun2.harvard.edu" Subject RE: Wald test: alternatives and small sample sizes Date Thu, 24 Jun 2010 10:20:06 +0200

```Hi John,

First of all, I apologize for my mistake: indeed it should have been Y regressed on X Z and Q.

As you proposed, I ran the test on the three coefficients simultaneously: chi2(  3) =   12.35, Prob > chi2 =    0.0063. While this confirms that there are differences between the two models in terms of those three variables, I cannot tell which ones are different and which ones are not (which I need as I have three hypotheses, one for each variable, in which I claim that two effects will be the same and one will be different).

Kind regards,

Veroniek

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of John Antonakis
Sent: jeudi 24 juin 2010 9:34
To: statalist@hsphsun2.harvard.edu
Subject: Re: Wald test: alternatives and small sample sizes

Hi Veroniek:

You might not have enough power.  Try testing all three coefficients
that are common simultaneously:

test ([one_mean]x = [two_mean]x) ([one_mean]z = [two_mean]z)
([one_mean]q = [two_mean]q)

Note, you have y as a dependent variable and as an independent variable;
just to show you how to put more than 1 test in there I added q as a
predictor too:

Regress y x z q + controls if group = 1
Est store one
Regress y x z q + controls if group = 0
Est store two
Suest one two, Cluster(Nr_Co)

HTH,
J.

____________________________________________________

Prof. John Antonakis, Associate Dean
Department of Organizational Behavior
University of Lausanne
Internef #618
CH-1015 Lausanne-Dorigny
Switzerland

Tel ++41 (0)21 692-3438
Fax ++41 (0)21 692-3305

Faculty page:
http://www.hec.unil.ch/people/jantonakis

Personal page:
http://www.hec.unil.ch/jantonakis
____________________________________________________

On 24.06.2010 08:38, Collewaert V (MCFE) wrote:
> Dear Statalist,
>
> I am trying to estimate two models (on two subsamples) with SuEst and cluster option as both samples are related (they belong to the same ventures). Specifically:
>
> Regress Y X Y Z + controls if group = 1
> Est store one
> Regress Y X Y Z + controls if group = 0
> Est store two
> Suest one two, Cluster(Nr_Co)
>
> However (!) the control variables are different for each group (for instance I control for experience in group 1, but not in group 0, and control for tenure in group 0, but not in group 1), so I do not have the same model for both groups.
>
> X, Y and Z refer to three main constructs of interest to my study and are included in both models. One of my hypotheses is that construct X should have a stronger (and positive) effect on group 1's outcome than on group 0's outcome. I tried running a Wald test:
>
> Test [one_mean = two_mean] X
>
> However, results seem strange to me: X is highly significant in model (group) 1, but absolutely not significant in model (group) 2 and still the Wald test proclaims that both coefficients are equal (chi2(  1) =    1.09,  Prob > chi2 =    0.2966). Could the problem be my small sample sizes? (respectively 72 and 65) And if so, what alternatives could I try? Or should I use another test than the Wald test to test this kind of hypothesis?
>
> With kind regards,
>
> Veroniek
>
>
>
>
>
>
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```