I have a 1:4 matched dataset. One case (a brain tumor that responded to an experimental treatment) matched to four controls (a brain tumor that did not respond). Two continuous variables of interest are test (the level of a serum biomarker; this is a unit-less ratio, range 0.05-0.50) and ses (socioeconomic status, range 1-100). I want to know if test is simply a proxy for ses, or is test an independent predictor of response. I therefore look for an interaction of ses on test. Using -clogit- I find:
HTML Code:
clogit response c.test##c.ses, group(pairid) or
note: 6 groups (24 obs) dropped because of all positive or
      all negative outcomes.

Iteration 0:   log likelihood = -1874.6946  
Iteration 1:   log likelihood = -1874.6418  
Iteration 2:   log likelihood = -1874.6418  

Conditional (fixed-effects) logistic regression

                                                Number of obs     =      5,825
                                                LR chi2(3)        =       3.67
                                                Prob > chi2       =     0.2995
Log likelihood = -1874.6418                     Pseudo R2         =     0.0010

------------------------------------------------------------------------------
    response | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        test |   .1709451    .255565    -1.18   0.237     .0091264    3.201941
         ses |   .9962459   .0070151    -0.53   0.593      .982591    1.010091
             |
c.test#c.ses |   1.015837   .0245912     0.65   0.516     .9687646    1.065197
------------------------------------------------------------------------------
So, I interpret this to mean there is no statistically significant interaction of ses on test. I then look at -margins- and -marginsplot-
HTML Code:
quietly margins, at(ses=(1(10)100) test = (0.05(0.05)0.5))

. marginsplot, noci
Array
Graphically, there appears to be an interaction.

Any help with interpretation would be much appreciated.

Best
Richard