----- Original Message -----
From: "Nick Varian" <[email protected]>
To: <[email protected]>
Sent: Friday, November 14, 2003 5:51 AM
Subject: Re: st: beginnerXs ask about Xtlogit probabilities
> Scott,
> thanks for your help. Could you help me once more? I
> am a lit bite confused, because using xtlogit i got
> some p-value that means that may parameter is
> significant different from zero. After calculing mfx
> compute, they all turn to insignificant. What does its
> means? In which one should I believe?
>
>
I can't really help you with that, however you may find reporting the percentage
change in odds rather than the marginal effects to be insightful. -listcoef-
will conveniently provide you with the odds ratio and the percentage change in
odds.
For example:
. webuse union
(NLS Women 14-24 in 1968)
. xtlogit union age grade south year, i(id) fe nolog
note: multiple positive outcomes within groups encountered.
note: 2744 groups (14165 obs) dropped due to all positive or
all negative outcomes.
Conditional fixed-effects logistic regression Number of obs = 12035
Group variable (i): idcode Number of groups = 1690
Obs per group: min = 2
avg = 7.1
max = 12
LR chi2(4) = 68.46
Log likelihood = -4515.9536 Prob > chi2 = 0.0000
------------------------------------------------------------------------------
union | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
age | .0758677 .0960711 0.79 0.430 -.1124282 .2641637
grade | .0857237 .0418685 2.05 0.041 .0036629 .1677845
south | -.7469976 .1249048 -5.98 0.000 -.9918065 -.5021887
year | -.059335 .0967972 -0.61 0.540 -.249054 .1303839
------------------------------------------------------------------------------
. mfx compute, predict(pu0)
Marginal effects after clogit
y = Pr(union|fixed effect is 0) (predict, pu0)
= .16861097
------------------------------------------------------------------------------
variable | dy/dx Std. Err. z P>|z| [ 95% C.I. ] X
---------+--------------------------------------------------------------------
age | .0106352 .02044 0.52 0.603 -.029435 .050705 30.538
grade | .0120169 .03911 0.31 0.759 -.064646 .088679 12.7934
south*| -.099099 .32063 -0.31 0.757 -.727525 .529327 .381388
year | -.0083177 .01301 -0.64 0.522 -.033809 .017174 79.6184
------------------------------------------------------------------------------
(*) dy/dx is for discrete change of dummy variable from 0 to 1
. listcoef, p
clogit (N=12035): Percentage Change in Odds
Odds of: 1 vs 0
--------------------------------------------------
union | b z P>|z| %
-------------+------------------------------------
age | 0.07587 0.790 0.430 7.9
grade | 0.08572 2.047 0.041 9.0
south | -0.74700 -5.981 0.000 -52.6
year | -0.05934 -0.613 0.540 -5.8
--------------------------------------------------
With this, the interpretation is
For each additional grade the odds of being in a union increase by 9%
holding all other variables constant.
or,
Working in the south reduces the odds of being in a union by 53%
Hope this helps,
Scott
*
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