-contrast- function not finding variables that exist

[Leo Davis]

I am trying to contrast the variables "race" and "vaccine". Both variables contained negative value labels in the dataset. I changed this with
Code:
egen race = group(w5_best_race), label
egen vaccine = group(w5_nc_cvhadvac), label

I can run regressions with the new variables, however when I try contrast
Code:
contrast race@vaccine, effects
contrast vaccine@race, effects

I get the following output:
variable race not found
r(111);

and

variable vaccine not found
r(111);

respectively

Despite being able to use the variables in regression and view them with -tab- and see them in my variables list. They definitely exist.

[Roman Mostazir]

Can't see your regression code. Could it be the problem of factor variable notation? Example:

sysuse auto, clear


reg mpg rep78 foreign

      Source |       SS           df       MS      Number of obs   =        69
-------------+----------------------------------   F(2, 66)        =     10.05
       Model |   546.30058         2   273.15029   Prob > F        =    0.0002
    Residual |  1793.90232        66  27.1803382   R-squared       =    0.2334
-------------+----------------------------------   Adj R-squared   =    0.2102
       Total |   2340.2029        68  34.4147485   Root MSE        =    5.2135

------------------------------------------------------------------------------
         mpg | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
       rep78 |   1.219096   .7926102     1.54   0.129    -.3634013    2.801593
     foreign |   4.202036   1.692832     2.48   0.016     .8221878    7.581885
       _cons |   15.85898   2.509808     6.32   0.000     10.84799    20.86997
------------------------------------------------------------------------------


contrast rep78@foreign
factor rep78 not found in list of covariates

//Using fv notation:

reg mpg i.rep78 i.foreign

      Source |       SS           df       MS      Number of obs   =        69
-------------+----------------------------------   F(5, 63)        =      4.96
       Model |  661.189524         5  132.237905   Prob > F        =    0.0007
    Residual |  1679.01337        63  26.6510059   R-squared       =    0.2825
-------------+----------------------------------   Adj R-squared   =    0.2256
       Total |   2340.2029        68  34.4147485   Root MSE        =    5.1625

------------------------------------------------------------------------------
         mpg | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
       rep78 |
          2  |     -1.875   4.081284    -0.46   0.648     -10.0308    6.280795
          3  |  -1.922325   3.774126    -0.51   0.612    -9.464315    5.619665
          4  |  -1.111626   3.944633    -0.28   0.779    -8.994346    6.771095
          5  |   3.453704   4.215132     0.82   0.416    -4.969565    11.87697
             |
     foreign |
    Foreign  |   3.556584   1.736681     2.05   0.045     .0861046    7.027064
       _cons |         21   3.650411     5.75   0.000     13.70524    28.29476
------------------------------------------------------------------------------

contrast rep78@foreign, effects

Contrasts of marginal linear predictions

Margins: asbalanced

-------------------------------------------------
              |         df           F        P>F
--------------+----------------------------------
rep78@foreign |
    Domestic  |          4        1.68     0.1655
     Foreign  |          4        1.68     0.1655
       Joint  |          4        1.68     0.1655
              |
  Denominator |         63
-------------------------------------------------

---------------------------------------------------------------------------------------
                      |   Contrast   Std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
        rep78@foreign |
(2 vs base) Domestic  |     -1.875   4.081284    -0.46   0.648     -10.0308    6.280795
 (2 vs base) Foreign  |     -1.875   4.081284    -0.46   0.648     -10.0308    6.280795
(3 vs base) Domestic  |  -1.922325   3.774126    -0.51   0.612    -9.464315    5.619665
 (3 vs base) Foreign  |  -1.922325   3.774126    -0.51   0.612    -9.464315    5.619665
(4 vs base) Domestic  |  -1.111626   3.944633    -0.28   0.779    -8.994346    6.771095
 (4 vs base) Foreign  |  -1.111626   3.944633    -0.28   0.779    -8.994346    6.771095
(5 vs base) Domestic  |   3.453704   4.215132     0.82   0.416    -4.969565    11.87697
 (5 vs base) Foreign  |   3.453704   4.215132     0.82   0.416    -4.969565    11.87697
---------------------------------------------------------------------------------------

[Nick Cox]

As Roman Mostazir points out, the contrast command (not function) expects a termlist and bare variable names will not work unless they have been used previously in an estimation command using factor variable notation.

[Leo Davis]

Thank you Roman Mostazir and Nick Cox, I was doing multinomial logistic regression with the two variables before. After running a linear regression with the factor variable notation the contrast command worked fine.