About AmyR

AmyR · ‎05-04-2021

And full code is below: libname amy '/folders/myfolders/COVID/Updated_05042021'; proc mixed data=amy.restructured_05042021; 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 ResilTot 105.12 time_rev*ResilTot 105.12/e; estimate 'moderate resilience' time_rev 1 ResilTot 135.5 time_rev*ResilTot 135.5/e; estimate 'high resilience' time_rev 1 ResilTot 157.92 time_rev*ResilTot 157.92/e; run; Resilience is at 16th, 50th, and 84th percentiles.

AmyR · ‎05-04-2021

Thanks! Results are included as a PDF.

AmyR · ‎05-04-2021

@jiltao @SteveDenham Thanks for your continued help with this. I ran three estimate statements as I noted in my previous post: estimate 'low resilience at time 1' time_rev 1 ResilTot 94.50 time_rev*ResilTot 94.50/e; estimate 'moderate resilience at time 1' time_rev 1 ResilTot 135 time_rev*ResilTot 135/e; estimate 'high resilience at time 1' time_rev 1 ResilTot 162.5 time_rev*ResilTot 162.5/e; I am still getting significant time by resilience interactions but non-significant conditional effects. Do you have any suggestions about how I can correctly derive the conditional effects? Thanks again.

AmyR · ‎04-29-2021

This makes sense. Thanks @SteveDenham . To confirm, the three estimate statements would be: estimate 'low resilience at time 1' time_rev 1 ResilTot 94.50 time_rev*ResilTot 94.50/e; estimate 'moderate resilience at time 1' time_rev 1 ResilTot 135 time_rev*ResilTot 135/e; estimate 'high resilience at time 1' time_rev 1 ResilTot 162.5 time_rev*ResilTot 162.5/e; Is this correct? Thanks again.

AmyR · ‎04-29-2021

Thank you @SteveDenham . I am trying to produce the effect of time at different different levels of resilience. Is the code you suggested achieving this? Or is it just producing the effect of resilience on depression at time 1? In other forum posts, I understood the "1" after time to represent a one unit increase in time but perhaps I am mistaken. Can you please clarify?

AmyR · ‎04-28-2021

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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Re: Continuous by continuous interaction using Proc Mixed

Re: Continuous by continuous interaction using Proc Mixed

Re: Continuous by continuous interaction using Proc Mixed

Re: Continuous by continuous interaction using Proc Mixed

Re: Continuous by continuous interaction using Proc Mixed

Continuous by continuous interaction using Proc Mixed

Re: Continuous by continuous interaction using Proc Mixed

Re: Continuous by continuous interaction using Proc Mixed

Re: Continuous by continuous interaction using Proc Mixed

Re: Continuous by continuous interaction using Proc Mixed

Re: Continuous by continuous interaction using Proc Mixed

Continuous by continuous interaction using Proc Mixed