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Re: st: Obtaining 95%CI for marginal effect
From
Steven Samuels <[email protected]>
To
[email protected]
Subject
Re: st: Obtaining 95%CI for marginal effect
Date
Sun, 6 Feb 2011 08:30:38 -0500
Nur-
Use -adjust- with the -ci- option. The fitted value of y is not a
"marginal effect"; for -regress- or (-svy: regress-) the default
marginal effects are the regression coefficients.
*********************
sysuse auto, clear
xi: reg weight price turn i.foreign
adjust price turn, by(foreign), se ci
******************
Steve
[email protected]
On Feb 6, 2011, at 7:02 AM, Nur Hafidha Hikmayani wrote:
Dear all,
I've been running some regression models using -svy- and estimating
its marginal effect using -mfx- (I use Stata 10.1).
I wonder how can I get the 95% CI for the marginal effects (y)?
The output for regression and its marginal effect are as follows:
. xi: svy: reg GH i.medgrp exgrp chronic nummed gp
------------------------------------------------------------------------------
| Linearized
GH | Coef. Std. Err. t P>|t| [95% Conf.
Interval]
-------------
+----------------------------------------------------------------
_Imedgrp_1 | 4.429839 3.56263 1.24 0.214 -2.564628
11.42431
_Imedgrp_2 | 8.333728 3.633545 2.29 0.022 1.200035
15.46742
_Imedgrp_3 | 10.05818 3.773961 2.67 0.008 2.648813
17.46755
exgrp | -8.916839 1.89046 -4.72 0.000 -12.62835
-5.205324
chronic | -10.31767 1.936802 -5.33 0.000 -14.12017
-6.515169
nummed | -1.063043 .3452676 -3.08 0.002 -1.740902 -.
3851831
gp | -4.347845 1.773649 -2.45 0.014 -7.830027
-.865663
_cons | 83.19335 3.520136 23.63 0.000 76.28231
90.10438
------------------------------------------------------------------------------
. mfx, at(mean _Imedgrp_1=0 _Imedgrp_2=0)
Marginal effects after svy:regress
y = Fitted values (predict)
= 53.085624
------------------------------------------------------------------------------
variable | dy/dx Std. Err. z P>|z| [ 95%
C.I. ] X
---------
+--------------------------------------------------------------------
_Imedg~1*| 4.429839 3.56263 1.24 0.214 -2.55279
11.4125 0
_Imedg~2*| 8.333728 3.63354 2.29 0.022 1.21211
15.4553 .379185
_Imedg~3*| 10.05818 3.77396 2.67 0.008 2.66136
17.455 0
exgrp*| -8.916839 1.89046 -4.72 0.000 -12.6221
-5.21161 .762312
chronic*| -10.31767 1.9368 -5.33 0.000 -14.1137
-6.52161 .83752
nummed | -1.063043 .34527 -3.08 0.002 -1.73975 -.386331
6.69376
gp*| -4.347845 1.77365 -2.45 0.014 -7.82413 -.
871558 .472814
------------------------------------------------------------------------------
(*) dy/dx is for discrete change of dummy variable from 0 to 1
Any help is much appreciated,
Thanks,
hafida-
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