BookmarkSubscribeRSS Feed
Jognnewsas
Calcite | Level 5

I have a dataset (see attached), which basically involves 4 treatments for a chemotherapy drug. Samples were taken from 2 biopsy locations, and biopsy were taken at 2 time points. So biopsy location and time are nested within subject, and thus each subject has 4 data points (from 2 biopsy locations and 2 time points). The objective is to study treatment difference.

time is 2-level factor (Day 4, Day 10)

biopsysite is 2-level factor (S1 and S2)

trt is 4-level factor (A, B, C, D)

An exmple part of the dataet looks like:

pid trt  time   biopsysite      y age

P2   A DAY 4           S1 -0.122  49

P2   A DAY 4           S2 -0.442  49

P2   A DAY 10          S1  0.229  49

P2   A DAY 10          S2 -0.007  49

P8   B DAY 4           S2  0.748  62

P8   B DAY 4           S1  0.086  62

P8   B DAY 10          S2  0.090  62

P8   B DAY 10          S1  0.076  62

:

:

:

I would like to fit a mixed model with age, time, trt and time by trt as fixed factor. "time" as repeated measure using AR1(), and "biopsysite" as random with compound symmetry covariance structure between the 2 biopsy locations.

How should I specify the mixed model? Is the following correct?

proc mixed;

  class pid trt time biopsysite;

  model y = age trt time trt*time / s;

  random biopsysite / type=cs subject=pid g;

  repeated / type=ar(1) subject=pid*biopsysite r;

  lsmeans trt*time/cl pdiff;

run;

Or what about this one, does it make sense?

proc mixed data=test;
class time trt pid biopsysite;
model y=age time trt time*trt/s;
random biopsysite/type=cs  g;
repeated pid / type=ar(1) r;

lsmeans trt*time / cl pdiff alpha=0.2;

run;



4 REPLIES 4
trekvana
Calcite | Level 5

i am thinking

proc mixed data=test;
class time trt pid biopsysite;
model y=age time trt time*trt/s;
random biopsysite /  type=cs subject=pid  g;
repeated time / type=ar(1) subject=pid r;

lsmeans trt*time / cl pdiff alpha=0.2;

run;

Jognnewsas
Calcite | Level 5

Thanks for suggestion. The reason I was using "subject=pid*biopsysite" in repeated statement was because the 2 time points thar were repeated were per each biopsy site, by specifying pid*biopsite intereaction, I was making sure the ar(1) covariance structure is applied to the 2 time point within biopsy site within subject. Accoording to MIXED manual:

"use the SUBJECT= option to define the blocks of and the TYPE= option to define their covariance structure"

The block of R in my example is within biopsy site within subject.

Am I understanding this correctly?

Thanks

trekvana
Calcite | Level 5

ah in that case do repeated time / type=ar(1) subject=biopsysite(pid)

the subject=biopsysite(pid) specifies that each biopsysite is nested with each pid. you may also want to try random intercept / type=un subject=pid that way you are fitting a random intercept for each person as well as an ar(1) covariance structure for the time points

this ultimately gives you a hybrid covariance structure. i can't think of the complete details off the top of my head (i'll have to reference back to my old school notes if you want more info)

cheers

Jognnewsas
Calcite | Level 5

Thank you very much!

SAS Innovate 2025: Register Now

Registration is now open for SAS Innovate 2025 , our biggest and most exciting global event of the year! Join us in Orlando, FL, May 6-9.
Sign up by Dec. 31 to get the 2024 rate of just $495.
Register now!

What is ANOVA?

ANOVA, or Analysis Of Variance, is used to compare the averages or means of two or more populations to better understand how they differ. Watch this tutorial for more.

Find more tutorials on the SAS Users YouTube channel.

Discussion stats
  • 4 replies
  • 1586 views
  • 3 likes
  • 2 in conversation