plot predicted values from modeled data with transformed variables

[pamplemousse822]

i want to plot outcome over time using predicted outcomes for an "average" observation from a model with transformed time variables (time^2). This works if I include the transformed variable in the model without calling in a new variable (e.g., time time*time). How can I make this work if i want to call in a new variable (vs. time time_sq, where time_sq=time*time)? Thanks! 

	*version 1: age age*age.... code works!;
	proc genmod data=dat; 
		class idno male edu; 
		model score= age|x age*age male edu_4; 
		repeated subject=idno; 
		weight w;
		store contcont; 
	run;

	data scoredata; *set covs to ref or mean; 
		male=0;
		edu=0;
		do x = 12, 18;
		do age = 70 to 100 by 1; 
			output; 
		end; end;
	run; 

	proc plm source=contcont; 
		 score data=scoredata out=plotdata predicted=pred lclm=lower uclm=upper; 
	run; 

	proc sgplot data=plotdata; 
		band x=age upper=upper lower=lower / group=x transparency=0.5; 
		series x=age y=pred / group=x; 
		yaxis label="score"; 
	run;

Version 1 (age age*age in model)

*version 2 (age age_sq)...code doesn't work;
	data dat2; 
		set dat; 
		age_sq=age*age; 
	run; 

	proc genmod data=dat2; 
		class idno male edu; 
		model score= age|x age_sq male edu_4; 
		repeated subject=idno; 
		weight w;
		store contcont; 
	run;

	data scoredata; *set covs to ref or mean; 
		male=0;
		edu=0;
		age_sq=6783; *mean value.. i have also tried omitting this and proc plm won't run because it needs all the variables;
		do x = 12, 18;
		do age = 70 to 100 by 1; 

			output; 
		end; end;
	run; 

	proc plm source=contcont; 
		 score data=scoredata out=plotdata predicted=pred lclm=lower uclm=upper; 
	run; 

	proc sgplot data=plotdata; 
		band x=age upper=upper lower=lower / group=x transparency=0.5; 
		series x=age y=pred / group=x; 
		yaxis label="score"; 
	run;

Version 2 (age age_sq in model)

[sbxkoenk]

Maybe I don't get it right ...

but shouldn't you replace (in your second code block) this piece of code

data scoredata; *set covs to ref or mean; 
	male=0;
	edu=0;
	age_sq=6783; *mean value.. i have also tried omitting this and proc plm won't run because it needs all the variables;
	do x = 12, 18;
	do age = 70 to 100 by 1; 

		output; 
	end; end;
run; 

with this piece of code

data scoredata; *set covs to ref or mean; 
	male=0;
	edu=0;
*age_sq=6783; *mean value.. i have also tried omitting this and proc plm won't run because it needs all the variables;
	do x = 12, 18;
	do age = 70 to 100 by 1; 
        age_sq = age*age;
		output; 
	end; end;
run; 

??

Koen

[pamplemousse822]

yes that works! my issue is that i am trying to use splined terms, so i have new age variables, like age2, age3, age4 from proc transreg.... and i dont know how to incorporate those new terms.

[ballardw]

---

@pamplemousse822 wrote:
yes that works! my issue is that i am trying to use splined terms, so i have new age variables, like age2, age3, age4 from proc transreg.... and i dont know how to incorporate those new terms.

---

I don't think Proc PLM will allow you to use variables that weren't in the original model.

You may be skipping out  on a clear description of what you are attempting. Perhaps you want to rename Age2 as Age and run PLM to create set with that variable as the age? Then rename Age3 ?

You should be able to do that as a data set option on the SCORE statement.

Something like:

score data=yourdataset (rename=(age2=age)) out=age2_scored_set /*other score options*/ ;

[sbxkoenk]

---

@pamplemousse822 wrote:
yes that works! my issue is that i am trying to use splined terms, so i have new age variables, like age2, age3, age4 from proc transreg.... and i dont know how to incorporate those new terms.

---

There's no need to use PROC TRANSREG to construct your splined terms.
You can use the SPLINE option in the EFFECT statement to generate spline effects.
See here : 
Regression with restricted cubic splines in SAS
By Rick Wicklin on The DO Loop April 19, 2017
https://blogs.sas.com/content/iml/2017/04/19/restricted-cubic-splines-sas.html

See also this usage note :
Usage Note 57975: Understanding splines in the EFFECT statement
https://support.sas.com/kb/57/975.html

For even more info, go here :
https://blogs.sas.com/content/?s=effect+spline

Koen