Stata Technical Bulletin
31
WhiteCol I
|
white I ed I |
4.813311 1.423556 1.035201 |
4.34508 |
1.741 3.011 1.837 |
0.082 0.003 0.066 |
.8204383 1.131219 |
28.23852 1.791439 1.074119 |
|
Prof I white I |
5.896191 |
4.451944 |
2.350 |
0.019 |
1.342357 |
— 25.89852 |
|
ed I |
2.178969 |
.2497737 |
6.795 |
0.000 |
1.740518 |
2.72787 |
|
exper I |
1.036294 |
.0186916 |
1.977 |
0.048 |
1.000299 |
1.073584 |
(Outcome Occ==Menial is the comparison group)
The standard Stata output allows you to immediately determine the factor change in the odds of each outcome category relative
to the comparison group Menial. The output does not include comparisons among other outcomes, such as BlueCol versus
Craft. Iistcoef provides all possible comparisons. Since this can generate extensive output, we illustrate two options that limit
which coefficients are listed. By specifying the variable ed, only coefficients for ed are listed. The option pv(.05) excludes
from printing any contrast that is not significant at the .05 level. Note that the coefficients below correspond to those listed
above (for example, the effect of ed on the odds of Prof versus Menial is 2.179 in both sets of output):
. Iistcoef ed, pv(.0δ)
mlogit (N=337): Factor Change in the Odds of occ when P>∣z∣ < 0.05
Variable: ed (sd= 2.94643)
|
Odds comparing I Group 1 - Group 2 I |
b |
z |
P>∣z∣ |
e^b |
e^bStdX |
|
— | |||||
|
BlueCol -Craft I |
-0.19324 |
-2.494 |
0.013 |
0.8243 |
0.5659 |
|
BlueCol -WhiteCol I |
-0.45258 |
-4.425 |
0.000 |
0.6360 |
0.2636 |
|
BlueCol -Prof I |
-0.87828 |
-8.735 |
0.000 |
0.4155 |
0.0752 |
|
Craft -BlueCol I |
0.19324 |
2.494 |
0.013 |
1.2132 |
1.7671 |
|
Craft -WhiteCol I |
-0.25934 |
-2.773 |
0.006 |
0.7716 |
0.4657 |
|
Craft -Prof I |
-0.68504 |
-7.671 |
0.000 |
0.5041 |
0.1329 |
|
Whitecol-BlueCol I |
0.45258 |
4.425 |
0.000 |
1.5724 |
3.7943 |
|
WhiteCol-Craft I |
0.25934 |
2.773 |
0.006 |
1.2961 |
2.1471 |
|
WhiteCol-Prof I |
-0.42569 |
-4.616 |
0.000 |
0.6533 |
0.2853 |
|
WhiteCol-Menial I |
0.35316 |
3.011 |
0.003 |
1.4236 |
2.8308 |
|
Prof -BlueCol I |
0.87828 |
8.735 |
0.000 |
2.4067 |
13.3002 |
|
Prof -Craft I |
0.68504 |
7.671 |
0.000 |
1.9838 |
7.5264 |
|
Prof -WhiteCol I |
0.42569 |
4.616 |
0.000 |
1.5307 |
3.5053 |
|
Prof -Menial I |
0.77885 |
6.795 |
0.000 |
2.1790 |
9.9228 |
|
Menial -WhiteCol I |
-0.35316 |
-3.011 |
0.003 |
0.7025 |
0.3533 |
|
Menial -Prof I |
-0.77885 |
-6.795 |
0.000 |
0.4589 |
0.1008 |
Example with zip and zinb
For the zip and zinb models, the output of Iistcoef makes it much simpler to be sure about the proper interpretation.
In the standard output from zip, which follows, the direction of effects can be difficult to determine.
. zip art fem mar kidδ phd ment, inf(fem mar kidδ phd ment) nolog
Zero-inflated poisson regression Number of obs = 91δ
Nonzero obs = 640
|
Inflation model = logit Log likelihood = -1604.773 |
Zero obs = LR chi2(5) Prob > chi2 = |
275 78.56 0.0000 | |||||
|
— |
art I |
Coef. |
Std. Err. |
z |
P>∣z∣ |
[957. Conf. |
— Interval] |
|
— |
— | ||||||
|
art |
I |
-.2091446 |
.0634047 |
-3.299 |
0.001 |
-.3334155 |
-.0848737 |
|
mar I |
.103751 |
.071111 |
1.459 |
0.145 |
-.035624 |
.243126 | |
|
kid5 I |
-.1433196 |
.0474293 |
-3.022 |
0.003 |
-.2362793 |
-.0503599 | |
|
phd I |
-.0061662 |
.0310086 |
-0.199 |
0.842 |
-.066942 |
.0546096 | |
|
ment I |
.0180977 |
.0022948 |
7.886 |
0.000 |
.0135999 |
.0225955 | |
|
.cons I |
.6408391 |
.1213072 |
5.283 |
0.000 |
.4030814 |
.8785967 | |
∙+∙