do glm with two data sets
On Wed, 2005-08-17 at 17:22 -0500, Sundar Dorai-Raj wrote:
Hu, Ying (NIH/NCI) wrote:
I have two data sets:
File1.txt:
Name id1 id2 id3 ...
N1 0 1 0 ...
N2 0 1 1 ...
N3 1 1 -1 ...
...
File2.txt:
Group id1 id2 id3 ...
G1 1.22 1.34 2.44 ...
G2 2.33 2.56 2.56 ...
G3 1.56 1.99 1.46 ...
...
I like to do:
x1<-c(0,1,0,...)
y1<-c(1.22,1.34, 2.44, ...)
z1<-data.frame(x,y)
summary(glm(y1~x1,data=z1)
But I do the same thing by inputting the data sets from the two files
e <- read.table("file1.txt", header=TRUE,row.names=1)
g <- read.table("file2.txt", header=TRUE,row.names=1)
e1<-exp[1,]
g1<-geno[1,]
d1<-data.frame(g, e)
summary(glm(e1 ~ g1, data=d1))
the error message is
Error in model.frame(formula, rownames, variables, varnames, extras,
extranames, :
invalid variable type
Execution halted
Thanks in advance,
Ying
Hi Ying, That error message is likely caused by having a data.frame on the right hand side (rhs) of the formula. You can't have a data.frame on the rhs of a formula and g1 is still a data frame even if you only choose the first row, e.g.: dat <- as.data.frame(matrix(100, 10, 10)) class(dat[1, ]) [1] "data.frame" You could try: glm(e1 ~ ., data=g1[1, ]) and see if that works, but as Sundar notes, your post is a little difficult to follow, so this may not do what you were trying to achieve. HTH Gav
You have several inconsistencies in your example, so it will be difficult to figure out what you are trying to accomplish.
> e <- read.table("file1.txt", header=TRUE,row.names=1)
> g <- read.table("file2.txt", header=TRUE,row.names=1)
> e1<-exp[1,]
What's "exp"? Also it's dangerous to use an R function as a variable name. Most of the time R can tell the difference, but in some cases it cannot.
> g1<-geno[1,]
What's "geno"?
> d1<-data.frame(g, e)
d1 is now e and g cbind'ed together?
> summary(glm(e1 ~ g1, data=d1))
Are "e1" and "g1" elements of "d1"? From what you've told us, I don't know where the error is occurring. Also, if you are having errors, you can more easily isolate the problem by doing: fit <- glm(e1 ~ g1, data = d1) summary(fit) This will at least tell you the problem is in your call to "glm" and not "summary.glm". --sundar P.S. Please (re-)read the POSTING GUIDE. Most of the time you will figure out problems such as these on your own during the process of creating a reproducible example.
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