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RE: st: RE: question from statalist
Just to see if it runs, I dropped all states with less than 2000 observations. Now all the SE are defined...and it doesn't look like stata drops any additional states because of multicollinearity... But it gives the same error:
. xi3: mlogit prod_type female_o ///
> fico ltv dti income loanamount loanterm ///
> ba_new f_min_arm5 t10_min_t1 e.state
e.state _Istate_4-53 (naturally coded; _Istate_4 omitted)
Iteration 0: log likelihood = -72881.502
Iteration 1: log likelihood = -55904.913
Iteration 2: log likelihood = -49007.083
Iteration 3: log likelihood = -47984.956
Iteration 4: log likelihood = -47889.198
Iteration 5: log likelihood = -47887.349
Iteration 6: log likelihood = -47887.345
Iteration 7: log likelihood = -47887.345
Multinomial logistic regression Number of obs = 133586
LR chi2(60) = 49988.31
Prob > chi2 = 0.0000
Log likelihood = -47887.345 Pseudo R2 = 0.3429
------------------------------------------------------------------------------
prod_type | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
p2 |
female_only | -.1555133 .0297789 -5.22 0.000 -.2138789 -.0971477
fico | -.000158 .0002554 -0.62 0.536 -.0006586 .0003427
ltv | -.0117513 .0010367 -11.34 0.000 -.0137832 -.0097195
dti | .0010724 .0012078 0.89 0.375 -.0012948 .0034395
income | .0001198 .0000953 1.26 0.209 -.000067 .0003067
loanamount | .0027244 .0000848 32.13 0.000 .0025581 .0028906
loanterm | .3048393 .0059386 51.33 0.000 .2931999 .3164787
ba_new | 1.380727 .1570039 8.79 0.000 1.073006 1.688449
f_min_arm5 | 3.34822 .2489538 13.45 0.000 2.860279 3.836161
t10_min_t1 | -.2526719 .0454174 -5.56 0.000 -.3416883 -.1636555
_Istate_6 | 1.177903 .0375687 31.35 0.000 1.104269 1.251536
_Istate_9 | -.4211162 .1363362 -3.09 0.002 -.6883301 -.1539022
_Istate_12 | .1748989 .0508363 3.44 0.001 .0752615 .2745363
_Istate_13 | .0120183 .0621117 0.19 0.847 -.1097183 .1337549
_Istate_17 | .5266333 .0624313 8.44 0.000 .4042702 .6489965
_Istate_20 | -.6538387 .1589123 -4.11 0.000 -.9653011 -.3423762
_Istate_24 | .7937781 .0586172 13.54 0.000 .6788905 .9086657
_Istate_25 | -.2993312 .0892851 -3.35 0.001 -.4743268 -.1243355
_Istate_29 | -.6722612 .1141442 -5.89 0.000 -.8959798 -.4485427
_Istate_32 | .9195407 .0929692 9.89 0.000 .7373244 1.101757
_Istate_34 | -.5387866 .1017824 -5.29 0.000 -.7382764 -.3392967
_Istate_36 | -.6020304 .0828407 -7.27 0.000 -.7643951 -.4396657
_Istate_37 | -.2893397 .0708244 -4.09 0.000 -.428153 -.1505265
_Istate_40 | -.9929478 .1939296 -5.12 0.000 -1.373043 -.6128529
_Istate_42 | -.4063065 .1287868 -3.15 0.002 -.658724 -.1538889
_Istate_45 | .0057848 .082172 0.07 0.944 -.1552694 .1668389
_Istate_47 | -.5059151 .1443456 -3.50 0.000 -.7888274 -.2230028
_Istate_48 | -.7562123 .0631341 -11.98 0.000 -.8799529 -.6324718
_Istate_51 | .6622584 .0612535 10.81 0.000 .5422037 .782313
_Istate_53 | .8346187 .0676625 12.34 0.000 .7020027 .9672348
_cons | -13.33689 .3214546 -41.49 0.000 -13.96693 -12.70686
-------------+----------------------------------------------------------------
p3 |
female_only | .2520734 .0216934 11.62 0.000 .2095551 .2945916
fico | -.005479 .0001709 -32.06 0.000 -.0058139 -.0051441
ltv | .1089525 .0014794 73.65 0.000 .106053 .111852
dti | -.0131825 .0011063 -11.92 0.000 -.0153509 -.0110141
income | -.0097414 .0003657 -26.64 0.000 -.0104581 -.0090246
loanamount | .0053394 .0001353 39.46 0.000 .0050742 .0056046
loanterm | -.30474 .0031175 -97.75 0.000 -.3108501 -.2986298
ba_new | 1.0459 .1243753 8.41 0.000 .8021284 1.289671
f_min_arm5 | 1.399249 .1952819 7.17 0.000 1.016503 1.781994
t10_min_t1 | -1.661645 .0393439 -42.23 0.000 -1.738758 -1.584533
_Istate_6 | 2.378287 .032999 72.07 0.000 2.31361 2.442964
_Istate_9 | -.1839164 .1083993 -1.70 0.090 -.3963751 .0285423
_Istate_12 | 1.200839 .0346214 34.68 0.000 1.132983 1.268696
_Istate_13 | -.0277285 .0458872 -0.60 0.546 -.1176658 .0622087
_Istate_17 | .0207768 .0673345 0.31 0.758 -.1111964 .1527499
_Istate_20 | -2.170635 .1792299 -12.11 0.000 -2.521919 -1.819351
_Istate_24 | 1.474792 .043018 34.28 0.000 1.390479 1.559106
_Istate_25 | .1024874 .0684801 1.50 0.134 -.0317311 .2367059
_Istate_29 | -.6156074 .0730468 -8.43 0.000 -.7587765 -.4724384
_Istate_32 | 2.030276 .0636586 31.89 0.000 1.905507 2.155044
_Istate_34 | .1079523 .0672633 1.60 0.109 -.0238814 .239786
_Istate_36 | -.0162838 .0647249 -0.25 0.801 -.1431423 .1105746
_Istate_37 | -.6099104 .0532916 -11.44 0.000 -.7143601 -.5054607
_Istate_40 | -3.112063 .2462253 -12.64 0.000 -3.594656 -2.62947
_Istate_42 | -1.117306 .1131833 -9.87 0.000 -1.339141 -.895471
_Istate_45 | -.6461894 .0765761 -8.44 0.000 -.7962758 -.4961031
_Istate_47 | -1.349594 .1318826 -10.23 0.000 -1.608079 -1.091109
_Istate_48 | -2.136153 .0655895 -32.57 0.000 -2.264706 -2.0076
_Istate_51 | 1.383357 .044693 30.95 0.000 1.295761 1.470954
_Istate_53 | 1.305855 .0550159 23.74 0.000 1.198026 1.413684
_cons | -.8105805 .213756 -3.79 0.000 -1.229535 -.3916265
------------------------------------------------------------------------------
(prod_type==p1 is the base outcome)
margeff
invalid syntax
-----Original Message-----
From: [email protected] [mailto:[email protected]] On Behalf Of Maarten buis
Sent: Thursday, April 09, 2009 12:05 PM
To: [email protected]
Subject: Re: st: RE: question from statalist
--- On Wed, 8/4/09, Paley, Irina wrote:
> I use your exact code for mlogit, adapted to my dataset, and when I
> run margeff I get that it's invalid syntax. What do you mean by
> leaving out reference category?
Say you want to controll for gender, than there are two dummies:
male (indicating who is male) and female (indicating who is female). These two variables contain superfluous information (if you know that someone isn't male than she is probably a female).
Because of that you can't add both variables in a regression, and you need to leave one of these two out of your model. The variable you leave out is called the reference category. The same is true for your state dummies, you need to leave one of the states out.
As you created your dummies using -xi3- this already happened, so this is not the problem. However, given that some of the state dummies have missing values on the standard errors suggests that there is still a problem with your model: you just don't have enough information in your data to add all the state dummies.
The easiest solution would be if you could find nearby states that are sort of similar to the problematic states, and merge these into "super states". So, States 50 54 2 30 46 and 72 are problematic (they either have a missing value on the standard error or they have been dropped outright due to
multiconlinearity) and asssume that state 50 is close to State 51, and state 54 to state 3 . Than you can create the "supper states" by making a copy of the variable state and use -recode-:
gen state2 = state
recode state2 (50=51) (54=3) etc.
And than you use state2 instead of state in your -mlogit- model.
Hope this helps,
Maarten
-----------------------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
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