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:
So, I interpret this to mean there is no statistically significant interaction of ses on test. I then look at -margins- and -marginsplot-
Graphically, there appears to be an interaction.
Any help with interpretation would be much appreciated.
Best
Richard
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 ------------------------------------------------------------------------------
HTML Code:
quietly margins, at(ses=(1(10)100) test = (0.05(0.05)0.5)) . marginsplot, noci
Graphically, there appears to be an interaction.
Any help with interpretation would be much appreciated.
Best
Richard
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