Generating plots for mixed-effect models (group, time, interaction terms)

[SpongeEvan]

Hello, I am trying to figure out how to generate plots from mixed-effects models from SAS. I am interested to see whether group show statistical differences on outcomes (measured at t0 and t2) at different time points (t0 and t2). Specifically, I am looking for a plot similar to ggeffects in R with predicted means, values between these two groups.

Please see the SAS codes below for the mixed-effect models. I tried several codes online (e.g., effect plot in the PROC PLM) but unable to generate the plots. Ideally, the plot will show timepoints at x-axis, pi/pdi at y-axis (they are the same measurement related at two points), and different lines representing two groups (variable BRIGHT). 

DATA Mixed1;
	SET anova_analysis2023;
	ARRAY A1{*} pit0 pdit2;
	DO TMP = 1 to 2; 
		TMPV = VNAME(A1{TMP});
		AVAL = A1{TMP};
		OUTPUT;
	END;
RUN;

PROC MIXED DATA = Mixed1;
	CLASS ID TMP(ref="1") BRIGHT(ref="0") POC/*IF CATEGORICAL COVARIATES ADD HERE*/;
	MODEL AVAL = TMP|BRIGHT POC other_op_inlife_t0/*IF CONTINUOUS COVARIATES HERE*/ / S E1 E2;
	REPEATED TMP / SUBJECT = ID TYPE = UN RCORR;
	LSMEANS TMP TMP*BRIGHT / CL DIFFS;
	TITLE1 “Mixed Model (Interaction) between group (BRIGHT) and Time”;
RUN;

 Some of the codes I have tested are as follows. Maybe I need to combine pit0 and pdit2 into one variable? Thanks for any advice. 

proc plm restore=PIPDIModel;                   /* use item store to create fit plots */
   effectplot fit(x=TMP plotby=BRIGHT);        /* panel */
   effectplot slicefit(x=TMP sliceby=BRIGHT);  /* overlay */
run;

proc sgplot data=Mixed1;
   scatter x=TMP y=AVAL / group=BRIGHT;
   series x=TMP y=AVAL / groupLC=BRIGHT curvelabel;
   legenditem type=line name="E" / label="Experiment" lineattrs=GraphData1; 
   legenditem type=line name="C" / label="Control" lineattrs=GraphData2(pattern=dash); 
   keylegend "E" "C";
run;

[Seadrago]

Hey so the dataset anova_analysis2023 is not included in the post. Hope this link helps https://blogs.sas.com/content/iml/2018/12/19/visualize-mixed-model.html