Date:  Thu, 19 Apr 2012 13:00:50 0500 
ReplyTo:  Warren Schlechte <Warren.Schlechte@TPWD.STATE.TX.US> 
Sender:  "SAS(r) Discussion" <SASL@LISTSERV.UGA.EDU> 
From:  Warren Schlechte <Warren.Schlechte@TPWD.STATE.TX.US> 
Subject:  Re: Proc GLIMMIX  Estimate Question 

InReplyTo:  <13DAEB09712F4D4382D11CB8FED4D26F8B46B3@UNMCEX3.unmcresforest.org> 
ContentType:  text/plain; charset="usascii" 
Thanks Robin.
Thought the answers didn't look quite right.
So, what I really need is:
Proc summary data=data2b noprint;
Var days;
output out=means mean=avg_days;
Run;
data _null_;
set means;
call symput("avg_days", put(avg_days,best32.));
run;
/* Other code */
estimate "S125: ndens=1, arch=1, Avg Days" intercept 1 ndens 1 0 0 arch
1 0 days &avg_days. / ilink cl;
Warren Schlechte
Learn how you can help Texas State Parks
Original Message
From: High, Robin R [mailto:rhigh@unmc.edu]
Sent: Thursday, April 19, 2012 12:47 PM
To: Warren Schlechte; SASL@LISTSERV.UGA.EDU
Subject: RE: Proc GLIMMIX  Estimate Question
Warren,
Yes, it would the estimate at days = 0, so need to add the mean value of
days, or specify the estimate to be computed for a specific value of
day, e.g.,
estimate "S125: ndens=1, arch=1, day=5" intercept 1 ndens 1 0 0 arch 1 0
days 5 / ilink cl;
Robin High
UNMC
Original Message
From: SAS(r) Discussion [mailto:SASL@LISTSERV.UGA.EDU] On Behalf Of
Warren Schlechte
Sent: Thursday, April 19, 2012 11:33 AM
To: SASL@LISTSERV.UGA.EDU
Subject: Proc GLIMMIX  Estimate Question
The following is the coding for a model I have run:
proc glimmix data=data2b ;
class ndens tank arch;
model out/in = arch ndens days /s dist=binomial link=logit e3
oddsratio;
random _residual_;
random intercept/subject=tank;
output out=binom_pout predicted(ilink noblup) =p resid(ilink noblup)=r;
estimate "S125" intercept 1 ndens 1 0 0 arch 1 0/ilink cl;
run;
Some items to notice:
* ndens, and arch are fixed categorical variables
* tank is a random categorical variable
* days is a fixed continuous variable
* the random residual statement is included to help capture
overdispersion in the binomial response.
What I am most interested in is this: Is the estimate statement giving
me the predicted value for my first treatment of density and
architecture at the average of the variable "days", and averaged across
all "tanks"? Is that a correct assumption, and if not, how do I change
the code to reflect the "average" conditions.
The reason I ask is, if I use the estimate statement, I get one estimate
of the predicted outcome. If instead, I use the output statement, then
create the summary statistics of the predicted values, I get a
substantially different answer. The value from the estimate statement
seems to reflect the estimate when days=0, not at the mean of days.
There is some unbalancedness within the design, but not so severe I
would expect to see the differences I see.
Thanks.
Warren Schlechte
HOH Fisheries Science Center
5103 Junction Hwy
Mt. Home, TX 78058
Phone 830.866.3356 x214
Fax 830.866.3549
Learn how you can help Texas State Parks <http://bit.ly/sVdilb>
