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Re: Wald test: alternatives and small sample sizes


From   John Antonakis <[email protected]>
To   [email protected]
Subject   Re: Wald test: alternatives and small sample sizes
Date   Thu, 24 Jun 2010 17:20:30 +0200

OK....then try the following after -suest-:

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

See the manual on -test-; the -mtest- gives you a multiple test option.

You might also want to control for multiple tests by doing the following:

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

-b- in this case is a Bonferonni adjustment (there are others; see the manual).

If you still don't find a significant result for the coefficient you are interested in you might not have enough power (precision) or the effect might not be there.

Best,
J.


____________________________________________________

Prof. John Antonakis, Associate Dean Faculty of Business and Economics
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 10:20, Collewaert V (MCFE) wrote:
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: [email protected] [mailto:[email protected]] On Behalf Of John Antonakis
Sent: jeudi 24 juin 2010 9:34
To: [email protected]
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 Faculty of Business and Economics
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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