I am running a model predicting depression (DASSDep) from the interaction of resilience (ResilTot) and time (time_rev) controlling for diagnostic group (DxGroup). I am treating time as continuous and it is measured over four time points, and resilience is also measured continuously. Even though my omnibus interaction is significant, the conditional effects I produced are not. Can someone please provide feedback on if I am producing the conditional effects correctly? And if I am, why might the conditional effects be non-significant and are there any follow-up tests I could conduct? Code is below: proc mixed data=amy.noanx; class PID DxGroup; model DASSDep = DxGroup ResilTot|time_rev /solution; store DepRes; random int/subject=PID; run; proc plm restore=DepRes; estimate 'low resilience' time_rev 1 time_rev*ResilTot 94.50, 'moderate resilience' time_rev 1 time_rev*ResilTot 135, 'high resilience' time_rev 1 time_rev*ResilTot 162.5/e; run;
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