Programming the statistical procedures from SAS

GLIMMIX Repeated measures multiple means comparison

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Contributor
Posts: 40

GLIMMIX Repeated measures multiple means comparison

Just want to make sure I'm "protected" when anallyzing all possible comparisons.

 

Study design (lamb feeding trial):

Effects of using ground juniper and feed urea in supplements fed to ewe lambs on growth, blood serum, xxx were evaluated. In a randomized design study, individually-penned lambs were fed xxx and of 1 of 8 supplements (fed separately from hay; 6 lambs/treatment) in a 4 × 2 factorial arrangement: 4 concentrations of juniper (15, 30, 45, or 60% of DM) and 2 levels of urea (1 or 3%). Lamb growth was evaluated on d 0, 5, 12, 19, 26, 33, and 40. Blood serum evaluated on d 6 to 8, 20 to 22, xxx.

 

A table will be produced that evaluates all possible comparisons.

Questions:

1. Is the following correct? Using Tukey adjustment?

2. Can I use "adjust = tukey" with PROC Glimmix (needd for some of my blood serum data)?

3. If JUN*UREA*Day is not significant, do I just drop it from the model & re-run it or just leave it in & just use the LSMeans of the full model? Probably doesn't matter, correct?

 

Note: all lambs have a different animal ID number.

 

PROC MIXED;

CLASS ID JUN UREA DAY;

MODEL supplementIntake = JUN UREA   JUN*UREA   JUN*UREA*DAY;

REPEATED DAY/SUBJECT=ID    TYPE = TOEPH (or other);

LSMEANS  JUN  UREA   JUN*UREA   JUN*UREA*DAY/PDIFF ADJUST=TUKEY;

RUN;QUIT;

Grand Advisor
Posts: 10,026

Re: GLIMMIX Repeated measures multiple means comparison

This may be more a comment on variable names. You have

Model supplementIntake =

 

Are you trying to model the intake? I would think that intake is more of something you are controlling and would be more of a fixed effect variable and that Growth or Blood serum measurement would be on the response side.

Contributor
Posts: 40

Re: GLIMMIX Repeated measures multiple means comparison

Supp intake is the depend. variable. Each supplement is different, thus we analyze intake of that supplement, along with growth, serum, etc.

Respected Advisor
Posts: 2,655

Re: GLIMMIX Repeated measures multiple means comparison

[ Edited ]

I would suggest adjust=simulate as opposed to Tukey as that method more accurately controls type 1 error.  

 

As far as the model statement, i suggest:

 

MODEL supplementIntake = JUN UREA   JUN*UREA  DAY JUN*DAY UREA*DAY JUN*UREA*DAY/solution;

 

and for the lsmeans statement, similarly incorporating DAY:

 

LSMEANS JUN UREA   JUN*UREA  DAY JUN*DAY UREA*DAY JUN*UREA*DAY/DIFF ADJUST=SIMULATE ADJDFE=ROW;

 

I would recommend not dropping any terms from the model due to "nonsignificance".

 

Steve Denham

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