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RE: st: run "cdsimeq" command and get error message "F ambiguous abbreviation"


From   "Sun, Yan (IFPRI)" <Y.SUN@cgiar.org>
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: st: run "cdsimeq" command and get error message "F ambiguous abbreviation"
Date   Thu, 23 Aug 2007 15:43:33 -0400

Thank you for your email. Here it is the command I am using: 

cdsimeq (lnR4rain simpson landdif ProdPblm AgExt) (D_off_female simpson
dependc)


                        NOW THE FIRST STAGE REGRESSIONS

      Source |       SS       df       MS              Number of obs =
252
-------------+------------------------------           F(  5,   246) =
0.90
       Model |  3.36395721     5  .672791442           Prob > F      =
0.4826
    Residual |  184.161499   246  .748623978           R-squared     =
0.0179
-------------+------------------------------           Adj R-squared =
-0.0020
       Total |  187.525456   251   .74711337           Root MSE      =
.86523

------------------------------------------------------------------------
------
    lnR4rain |      Coef.   Std. Err.      t    P>|t|     [95% Conf.
Interval]
-------------+----------------------------------------------------------
------
     simpson |   .1184274   .1826432     0.65   0.517    -.2413166
.4781714
     landdif |   .0036154   .0051364     0.70   0.482    -.0065014
.0137323
    ProdPblm |  -.2105545   .1662512    -1.27   0.207    -.5380119
.1169029
       AgExt |   .0096537   .0087856     1.10   0.273    -.0076509
.0269584
     dependc |   .0332848   .0425781     0.78   0.435    -.0505792
.1171489
       _cons |   12.42117   .3604348    34.46   0.000     11.71123
13.1311
------------------------------------------------------------------------
------

Iteration 0:   log likelihood = -143.86365
Iteration 1:   log likelihood = -141.70529
Iteration 2:   log likelihood = -141.69626
Iteration 3:   log likelihood = -141.69626

Probit regression                                 Number of obs   =
252
                                                  LR chi2(5)      =
4.33
                                                  Prob > chi2     =
0.5023
Log likelihood = -141.69626                       Pseudo R2       =
0.0151

------------------------------------------------------------------------
------
D_off_female |      Coef.   Std. Err.      z    P>|z|     [95% Conf.
Interval]
-------------+----------------------------------------------------------
------
     simpson |  -.0677971   .3016356    -0.22   0.822    -.6589921
.5233979
     landdif |  -.0052904   .0084477    -0.63   0.531    -.0218475
.0112667
    ProdPblm |   .3989428   .2881943     1.38   0.166    -.1659078
.9637933
       AgExt |   .0071777   .0139787     0.51   0.608      -.02022
.0345754
     dependc |  -.0779648   .0685734    -1.14   0.256    -.2123662
.0564366
       _cons |  -.9195571   .5760108    -1.60   0.110    -2.048518
.2094034
------------------------------------------------------------------------
------



              NOW THE SECOND STAGE REGRESSIONS WITH INSTRUMENTS




      Source |       SS       df       MS              Number of obs =
252
-------------+------------------------------           F(  5,   246) =
0.90
       Model |  3.36395721     5  .672791442           Prob > F      =
0.4826
    Residual |  184.161499   246  .748623978           R-squared     =
0.0179
-------------+------------------------------           Adj R-squared =
-0.0020
       Total |  187.525456   251   .74711337           Root MSE      =
.86523

------------------------------------------------------------------------
------
    lnR4rain |      Coef.   Std. Err.      t    P>|t|     [95% Conf.
Interval]
-------------+----------------------------------------------------------
------
I_D_off_fe~e |  -.4269214   .5461192    -0.78   0.435    -1.502587
.6487445
     simpson |   .0894834   .1890214     0.47   0.636    -.2828234
.4617901
     landdif |   .0013568   .0058259     0.23   0.816    -.0101181
.0128318
    ProdPblm |  -.0402373   .2736064    -0.15   0.883    -.5791474
.4986727
       AgExt |    .012718   .0098561     1.29   0.198     -.006695
.0321311
       _cons |   12.02859   .6717123    17.91   0.000     10.70555
13.35163
------------------------------------------------------------------------
------

Iteration 0:   log likelihood = -143.86365
Iteration 1:   log likelihood =  -142.6572
Iteration 2:   log likelihood = -142.65558
Iteration 3:   log likelihood = -142.65558

Probit regression                                 Number of obs   =
252
                                                  LR chi2(3)      =
2.42
                                                  Prob > chi2     =
0.4906
Log likelihood = -142.65558                       Pseudo R2       =
0.0084

------------------------------------------------------------------------
------
D_off_female |      Coef.   Std. Err.      z    P>|z|     [95% Conf.
Interval]
-------------+----------------------------------------------------------
------
  I_lnR4rain |  -.8678088   .8453643    -1.03   0.305    -2.524692
.7890749
     simpson |   .0885422   .3021884     0.29   0.770    -.5037362
.6808205
     dependc |  -.0535112   .0723519    -0.74   0.460    -.1953184
.0882959
       _cons |   10.34456   10.59304     0.98   0.329    -10.41741
31.10653
------------------------------------------------------------------------
------


         NOW THE SECOND STAGE REGRESSIONS WITH CORRECTED STANDARD ERRORS


F ambiguous abbreviation
r(111);

end of do-file

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Richard
Williams
Sent: Thursday, August 23, 2007 4:26 PM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: run "cdsimeq" command and get error message "F
ambiguous abbreviation"

At 02:18 PM 8/23/2007, Sun, Yan (IFPRI) wrote:
>Hi,
>I try to use "cdsimeq" to run simultaneous equations (one continuous 
>dependent variables and one dichotomous dependent variables), and got 
>error message "F ambiguous abbreviation, r(111)", so I am not able to 
>get the second stage regressions with corrected errors. But I do not 
>have any variables beginning with "F" in my regression variable lists, 
>how could I have F ambiguous abbreviation? Please help. Thanks.
>
>Yan
>IFPRI

It would help to give the exact command you used - and, if possible,
even better if you could provide a reproducible example.


-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
HOME:   (574)289-5227
EMAIL:  Richard.A.Williams.5@ND.Edu
WWW:    http://www.nd.edu/~rwilliam

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