Comparing subcategories between groups

[Agnes Weis]

Dear group members, I would like to ask whether you could suggest me a test for the following situation:

I have two groups (A and B). Both groups have data for a categorical variable called X that has 3 categories. I would like to test whether the answers for each of the category are different between two groups. For example, I want to know if the number of observations in the first category is significantly greater in group A compared to the number of observations in the same category in group B.

[Carlo Lazzaro]

Agnes:
assunng that the levels of your depenedent variable are not ordered, you may want to consider -mlogit- and its post estimation suite of commands:

. use "C:\Program Files\Stata17\ado\base\a\auto.dta"
(1978 automobile data)

. tabulate rep78 foreign , chi2 col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

    Repair |
    record |      Car origin
      1978 |  Domestic    Foreign |     Total
-----------+----------------------+----------
         1 |         2          0 |         2
           |      4.17       0.00 |      2.90
-----------+----------------------+----------
         2 |         8          0 |         8
           |     16.67       0.00 |     11.59
-----------+----------------------+----------
         3 |        27          3 |        30
           |     56.25      14.29 |     43.48
-----------+----------------------+----------
         4 |         9          9 |        18
           |     18.75      42.86 |     26.09
-----------+----------------------+----------
         5 |         2          9 |        11
           |      4.17      42.86 |     15.94
-----------+----------------------+----------
     Total |        48         21 |        69
           |    100.00     100.00 |    100.00

          Pearson chi2(4) =  27.2640   Pr = 0.000

. mlogit rep78 i.foreign

Iteration 0:   log likelihood = -93.692061  
Iteration 1:   log likelihood = -80.470733  
Iteration 2:   log likelihood = -78.986489  
Iteration 3:   log likelihood = -78.794109  
Iteration 4:   log likelihood = -78.748501  
Iteration 5:   log likelihood = -78.738643  
Iteration 6:   log likelihood = -78.736602  
Iteration 7:   log likelihood = -78.736144  
Iteration 8:   log likelihood = -78.736032  
Iteration 9:   log likelihood = -78.736009  
Iteration 10:  log likelihood = -78.736004  

Multinomial logistic regression                         Number of obs =     69
                                                        LR chi2(4)    =  29.91
                                                        Prob > chi2   = 0.0000
Log likelihood = -78.736004                             Pseudo R2     = 0.1596

------------------------------------------------------------------------------
       rep78 | Coefficient  Std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
1            |
     foreign |
    Foreign  |   -13.6844   1986.817    -0.01   0.995    -3907.774    3880.405
       _cons |  -2.602702   .7328328    -3.55   0.000    -4.039028   -1.166376
-------------+----------------------------------------------------------------
2            |
     foreign |
    Foreign  |   -13.6844   993.4086    -0.01   0.989    -1960.729    1933.361
       _cons |  -1.216408   .4025404    -3.02   0.003    -2.005373    -.427443
-------------+----------------------------------------------------------------
3            |  (base outcome)
-------------+----------------------------------------------------------------
4            |
     foreign |
    Foreign  |   2.197466   .7698095     2.85   0.004     .6886674    3.706265
       _cons |  -1.098617   .3849011    -2.85   0.004    -1.853009   -.3442246
-------------+----------------------------------------------------------------
5            |
     foreign |
    Foreign  |    3.70116   .9906909     3.74   0.000     1.759442    5.642879
       _cons |  -2.602577     .73279    -3.55   0.000    -4.038819   -1.166335
------------------------------------------------------------------------------

. test [5] ///I'm interested in testing if the coefficient -repairs=5- differsfrom zero for both domestic and foreign cars///

 ( 1)  [5]0b.foreign = 0
 ( 2)  [5]1.foreign = 0
       Constraint 1 dropped

           chi2(  1) =   13.96
         Prob > chi2 =    0.0002

/// or, put differently:///

. test [5]0b.foreign=[5]1.foreign

 ( 1)  [5]0b.foreign - [5]1.foreign = 0

           chi2(  1) =   13.96
         Prob > chi2 =    0.0002

.

[Agnes Weis]

Thank you so much! It worked perfectly.