Hi everyone,

I had a quick question. I am new to Stata, so please forgive me if this question seems silly. I am currently running a regression using NHIS data. I am looking at whether using different alternative medicine therapies is associated with an increased odds of developing eczema. In this example, I will use massage as the alternative medicine therapy. I added a co-variate to control for those who may use massage to treat eczema, which is represented by the variable "massage eczema" (it is binary - 0= did not use massage to treat eczema, 1= did use massage to treat eczema). However, when I run the regression, I get an error stating, "0.massageczema omitted because of collinearity."

Is there any way to work around this problem? I do need to control for those who use the therapy for eczema, as this would be a confounding variable.

I tried to look on the FAQ on how to post code, but the help dataex was not very clear. I have copied and pasted my output below, although I know it may be hard to read.

Code:
svy: logistic eczema i.massage i.massageczema i.sex i.race i.education age i.houseincome
(running logistic on estimation sample)

note: 0.massageczema omitted because of collinearity

Survey: Logistic regression

Number of strata   =       295                  Number of obs     =      3,509
Number of PSUs     =       569                  Population size   =  9,464,725
                                                Design df         =        274
                                                F(  11,    264)   =       2.95
                                                Prob > F          =     0.0010

--------------------------------------------------------------------------------
               |             Linearized
        eczema | Odds Ratio   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
     1.massage |   1.236095   .1598816     1.64   0.102     .9582202     1.59455
0.massageczema |          1  (omitted)
               |
           sex |
       Female  |   1.408807    .155003     3.12   0.002     1.134445    1.749524
               |
          race |
            1  |   1.145142   .2472934     0.63   0.531       .74856    1.751829
            2  |   1.241144    .562923     0.48   0.634     .5082126    3.031091
            3  |   1.306405   .4124466     0.85   0.398     .7017001    2.432225
            4  |   1.726738   .4454404     2.12   0.035     1.039133    2.869341
               |
     education |
            1  |   .7790274   .1379485    -1.41   0.160     .5497371    1.103953
            2  |   .8614225   .1350667    -0.95   0.342     .6326449    1.172931
               |
           age |   .9909397   .0027883    -3.23   0.001     .9854657    .9964442
               |
   houseincome |
            1  |   .8864313   .1281452    -0.83   0.405     .6668787    1.178266
            2  |   .7667886   .1397184    -1.46   0.146     .5356586    1.097648
               |
         _cons |   .2079644   .0387932    -8.42   0.000     .1440467    .3002444
--------------------------------------------------------------------------------
Note: _cons estimates baseline odds.
Note: 1 stratum omitted because it contains no population members.
Note: Strata with single sampling unit treated as certainty units.