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]

Wald test: alternatives and small sample sizes


From   "Collewaert V (MCFE)" <[email protected]>
To   "[email protected]" <[email protected]>
Subject   Wald test: alternatives and small sample sizes
Date   Thu, 24 Jun 2010 08:38:46 +0200

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/


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