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]

From |
"Collewaert V (MCFE)" <v.collewaert@maastrichtuniversity.nl> |

To |
"statalist@hsphsun2.harvard.edu" <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 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 > > > > > > > * > * 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/ * * 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/

**Follow-Ups**:**Re: Wald test: alternatives and small sample sizes***From:*John Antonakis <john.antonakis@unil.ch>

**References**:**Wald test: alternatives and small sample sizes***From:*"Collewaert V (MCFE)" <v.collewaert@maastrichtuniversity.nl>

**Re: Wald test: alternatives and small sample sizes***From:*John Antonakis <john.antonakis@unil.ch>

- Prev by Date:
**Re: st: RE: Large data set that won't open** - Next by Date:
**st: how to caculate the formulation in the attachment in the state?** - Previous by thread:
**Re: Wald test: alternatives and small sample sizes** - Next by thread:
**Re: Wald test: alternatives and small sample sizes** - Index(es):