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

So, I interpret this to mean there is no statistically significant interaction of

Graphically, there appears to be an interaction.

Any help with interpretation would be much appreciated.

Best

Richard

**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 ------------------------------------------------------------------------------

**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

Graphically, there appears to be an interaction.

Any help with interpretation would be much appreciated.

Best

Richard

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