Just as an addition, I highly suggest the original poster take a look
at:
JS Long (1998) Regression Models for Categorical and Limited Dependent
Variables.
JS Long & J Freese (2005) Regression Models for Categorical Dependent
Variables With Stata, 2nd Ed.
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Scott
Merryman
Sent: Thursday, October 23, 2008 7:39 AM
To: [email protected]
Subject: Re: st: Significance of Probit estimates versus marginal
effects
On Wed, Oct 22, 2008 at 8:11 PM, Kir1 <[email protected]> wrote:
> Hi All,
>
> A search on the statlist archives didn't turn up an answer to this.
> Can anyone help?
>
> When i run a probit I find the variable of interest statistically
> significant. However, once I list the marginal effects using
> 'margeff', the variable is not statistically significant anymore.
> (margeff, at(mean) same as mfx is still significant as the probit
> estimate, albeit at a different level of significance).
>
> What can i make of this?Is the effect of the variable significant or
> not? what is the different meaning of the significance of the probit
> estimate versus that of the marginal effect?
>
In addition:
"...the standard error of the marginal effect is obtained by the delta
method, which means that the standard error for the marginal effect of
one independent variable involves the whole variance-covariance matrix
from the estimation together with the appropriate entries from the
Jacobian. In other words, there is a lot of stuff that goes into the
calculation beyond just the standard error of the coefficient of that
variable, and these other things can cause it to be greater than 0.05,
even when the coefficient standard error is less than 0.05."
(From May Boggess <[email protected]>
http://www.stata.com/statalist/archive/2004-03/msg00142.html)
Scott
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