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# st: margins: error at values for factor do not sum to 1

 From Hanna Schwander To statalist@hsphsun2.harvard.edu Subject st: margins: error at values for factor do not sum to 1 Date Mon, 25 Feb 2013 17:22:57 +0100

Hi Statalists,

I'd like to know how the marginal effect of gender changes on my dependent dummy variable over time. I run a logit model
including a full factorial interaction between gender and year_dv.

The logit model works just fine, but I receive the error "at values for factor year_dv do not sum to 1" when stata tries to calculate the
marginal effects.
It must be related to the covariate, because if I calculate ME only for logit dv i.gender##year_dv i_educ_y, it works perfectly fine.

gender is a dummy variable (0:1) and year_dv is a categorical variable with values of 1976, 1983, 1990, 1993, 1996, 1997, ..., 2011.

I would appreciate any help or explanation what's going on.

best,
Hanna

logit dv i.gender##year_dv hhcomp AGE i.unempl i.retired i.couple i.selfempl i.educ_y if cnty2==4, rob
> ust

Iteration 0:   log pseudolikelihood =  -9811.722
Iteration 1:   log pseudolikelihood = -8447.6971
Iteration 2:   log pseudolikelihood = -8427.5904
Iteration 3:   log pseudolikelihood = -8427.4542
Iteration 4:   log pseudolikelihood = -8427.4542

Logistic regression                               Number of obs   =      14317
Wald chi2(32)   =    2086.81
Prob > chi2     =     0.0000
Log pseudolikelihood = -8427.4542                 Pseudo R2       =     0.1411

--------------------------------------------------------------------------------
|               Robust
dv |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
1.gender |   .0315729   .1357372     0.23   0.816    -.2344672     .297613
|
year_dv |
1978  |  -.7536955   .1605846    -4.69   0.000    -1.068435   -.4389555
1983  |  -.6530303   .1440718    -4.53   0.000    -.9354058   -.3706549
1989  |   .1768951   .1319218     1.34   0.180    -.0816668     .435457
1991  |   .8093866   .1381717     5.86   0.000      .538575    1.080198
1993  |   .8264365    .153616     5.38   0.000     .5253547    1.127518
1998  |   2.470491   .1973473    12.52   0.000     2.083697    2.857285
2000  |   1.913222   .1414099    13.53   0.000     1.636063     2.19038
2005  |  -.5515456   .1394236    -3.96   0.000    -.8248108   -.2782805
2006  |  -.6318867   .1457566    -4.34   0.000    -.9175644   -.3462089
2009  |   .5445553   .1391717     3.91   0.000     .2717837    .8173269
2010  |  -.0664371   .1215095    -0.55   0.585    -.3045913     .171717
2011  |  -1.277709   .1521589    -8.40   0.000    -1.575935   -.9794832
|
gender#year_dv |
1 1978  |   .0290359   .2115727     0.14   0.891     -.385639    .4437108
1 1983  |    .135529   .1932716     0.70   0.483    -.2432764    .5143344
1 1989  |  -.0226443   .1814511    -0.12   0.901     -.378282    .3329934
1 1991  |  -.0175356   .1901607    -0.09   0.927    -.3902438    .3551725
1 1993  |   .4637764   .2166843     2.14   0.032      .039083    .8884697
1 1998  |  -.3900139   .2615363    -1.49   0.136    -.9026156    .1225877
1 2000  |  -.0903408   .1906076    -0.47   0.636    -.4639249    .2832433
1 2005  |   .0909939   .1872374     0.49   0.627    -.2759847    .4579726
1 2006  |   .1630719   .1880115     0.87   0.386    -.2054239    .5315677
1 2009  |   .1353967   .1886154     0.72   0.473    -.2342827    .5050762
1 2010  |   .1808376   .1629267     1.11   0.267    -.1384929     .500168
1 2011  |   .1192825   .2067946     0.58   0.564    -.2860274    .5245924
|
hhcomp |    .023339   .0220796     1.06   0.290    -.0199362    .0666142
AGE |  -.0039472   .0014175    -2.78   0.005    -.0067255    -.001169
1.unempl |   .3955106    .095885     4.12   0.000     .2075794    .5834419
1.retired |  -.0081702   .0594042    -0.14   0.891    -.1246003    .1082598
1.couple |   -.155951   .0432974    -3.60   0.000    -.2408123   -.0710896
1.selfempl |  -.1637611   .0755383    -2.17   0.030    -.3118135   -.0157087
1.educ_y |   -.105405   .0448559    -2.35   0.019    -.1933209   -.0174891
_cons |   .2682743   .1204209     2.23   0.026     .0322536     .504295
--------------------------------------------------------------------------------

.
.
.         margins, dydx(gender) at(year_dv=(1976 1978 1983 1989 1991 1993 1998 2000 2001 2003 2005 2006
> 2009 2010 2011)) vsquish
at values for factor year_dv do not sum to 1
r(198);

end of do-file

PS: I am using Stata/IC 12.1 for Mac (64-bit Intel)
Revision 30 Jan 2013

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