Alright, I'll try to give some sample code. # create A with 2 levels - 2 and 4 > A<-c(rep(2,times=30),rep(4,times=42)) # make A a factor > A<-as.factor(A) #generate 72 random x points > x<-rnorm(72) #create different slopes & intercepts for A=2 and A=4 #add a random error term > y<-c(x[(1:30)]+1,2*x[(31:72)]-2)+rnorm(72,mean=0,sd=2) #use model y~A*x for lm (or glm) > test.lm<-lm(y~A*x) #check the output > summary(test.lm) This essentially creates something like my data set and uses the same model. In response to (1), I was just using 0/1 because these are codings for the 2 levels, correct? (i.e., when A=2 the dummy variable=0, when A=4 the dummy variable=1?). In response to (2), yes, I do want different slopes for the two categories (that is what I am interested in testing). If I export the data created above to JMP and run what I believe to be the same model, I get a different answer for my equations :( ------------------------------- Benjamin Ridenhour School of Biological Sciences Washigton State University P.O. Box 644236 Pullman, WA 99164-4236 Phone (509)335-7218 -------------------------------- "Nothing in biology makes sense except in the light of evolution." -T. Dobzhansky ----- Original Message ---- From: "Liaw, Andy" Sent: Tuesday, February 28, 2006 5:14:57 PM Subject: RE: [R] Help - lm, glm, aov results inconsistent with other stati stical package 1. You have levels(A) as "2" and "4", yet you showed equations for A=0 and A=1? 2. y = A + X + A*X means you're allowing the different groups of A to have different slopes. Probably not what you intended. 3. It's probably best to provide a small sample of the data (and R code) so we know how you got what you got. Andy From: Ben Ridenhour > > Hello, > > I 'm sure there must a be a simple explanation for what I'm > doing wrong but I am stumped. I am a novice R user and this > has shaken my confidence in what I'm doing! I am trying to > run a simple ANCOVA using the model y~A*x, where y and x are > continuous and A has two levels. Everything seems fine until > I compare the output with what I get from another statistical > package (JMP). JMP has the model y=A+x+A*x (this should be > the same as what I specified to R, correct?). In comparison > I get the line equations > > y = 7072.09-1024.94 x (for A=0) and > y = 7875.58-970.088 x (for A=1) > > from JMP. And from R I get > > y = 6276.7-1259.8 x (for A=0) and > y = 7867.5-1150.1 x (for A=1). > > Obviously, these aren't even close to the same answer. I've > tried this using glm(), lm(), and aov() and as expected they > all give the same answer. If I do > > >levels(A) > [1] "2" "4" > > which are the two levels of A. Why can't I get the same > answer from JMP as in R? This is very disturbing to me! > > Thanks, > Ben > > > ------------------------------- > Benjamin Ridenhour > School of Biological Sciences > Washigton State University > P.O. Box 644236 > Pullman, WA 99164-4236 > Phone (509)335-7218 > -------------------------------- > "Nothing in biology makes sense except in the light of evolution." > -T. Dobzhansky > > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > > ------------------------------------------------------------------------------ ------------------------------------------------------------------------------ [[alternative HTML version deleted]]