Re: st: Vuong test for nested linear models

[John Antonakis <John.Antonakis@unil.ch>]

Hi:

You don't need a Vuong test here. Because you are adding one parameter, 
the test of b3 = 0 is the test you want. That is simply the test of the 
significance of the parameter estimate. This is equivalent to the nested 
F-test:

sysuse auto
nestreg : reg price (mpg) (weight)

The F-change test for adding weight is equivalent to the t-test^2 of the 
parameter, i.e.,

dis (_b[weight]/_se[weight])^2

You can still use the lrtest after OLS.

reg price mpg
est store one
reg price mpg weight
est store two
lrtest one two

Best,
J.

__________________________________________

John Antonakis
Professor of Organizational Behavior
Director, Ph.D. Program in Management

Faculty of Business and Economics
University of Lausanne
Internef #618
CH-1015 Lausanne-Dorigny
Switzerland
Tel ++41 (0)21 692-3438
Fax ++41 (0)21 692-3305
http://www.hec.unil.ch/people/jantonakis

Associate Editor:
The Leadership Quarterly
Organizational Research Methods
__________________________________________

On 09.02.2014 19:33, Cindy wrote:
> Hi, do anyone know how to do Vuong test (Vuong 1989) for model 
selection of
> two nested linear models in Stata? It seems that people use Vuong test
> mostly for non-nested models. But Vuong (1989) covers both nested and
> non-nested models. Following are my two models:
>
> Model 1: Y=a0+a1X1+a2X2+e
> Model 2: Y=b0+b1X1+b2X2+b3X3+v
>
> Both models are OLS regressions. I need to test how significant the
> incremental adjusted R2 in model 2 is from adding X3 (my variable of
> interest) to model 1.
>
> Also, it seems that a likelihood ratio test could be used to test nested
> models, too. But when I looked up the code in stata (lrtest), it says 
that
> it’s applicable for maximum likelihood models only.
>
> Thank you very much!!
>
>
>
> --
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