Hi Annaële,
try to use the following:
lm1 <- lm(y~x, data=SDF1)
lm2 <- lm(y~Group*x, data=SDF1)
anova(lm1, lm2)
I hope this helps.
Best,
Dimitris
----
Dimitris Rizopoulos
Doctoral Student
Biostatistical Centre
School of Public Health
Catholic University of Leuven
Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/16/396887
Fax: +32/16/337015
Web: http://www.med.kuleuven.ac.be/biostat/
http://www.student.kuleuven.ac.be/~m0390867/dimitris.htm
----- Original Message -----
From: <asanquer@virbac.fr>
To: "s-news" <s-news@wubios.wustl.edu>
Sent: Tuesday, July 13, 2004 9:24 AM
Subject: [S] Ancova
Hello,
does someone could tell me what is the best way to perform an analysis
of
covariance.
I try :
summary(glm(y ~ Group * x, data=SDF1))
I obtain the following results:
Coefficients:
Value Std. Error t value
(Intercept) 58.714096 10.900908 5.3861657
Group1 13.723168 13.096083 1.0478835
Group2 -13.982561 7.852430 -1.7806666
x 2.114921 1.164596 1.8160129
Group1x -1.347520 1.440343 -0.9355554
Group2x 1.419042 0.815325 1.7404613
but I would like to have a p-value for the global group effect, how
can I
obtain it?
Thanks in advance,
Annaële Sanquer
--------------------------------------------------------------------
This message was distributed by s-news@lists.biostat.wustl.edu. To
unsubscribe send e-mail to s-news-request@lists.biostat.wustl.edu with
the BODY of the message: unsubscribe s-news
|