Hello R-Users!
I need a little help to build up a contingency table out of several
variables.
A-c(F,M,M,F,F,F,F,M,F,M,F,F)
B-c(0,0,0,0,0,0,1,1,1,1,0,1)
C-c(0,1,1,1,1,1,1,1,1,0,0,0)
ABC-as.data.frame(cbind(A,B,C))
ABC
A B C
1 F 0 0
2 M 0 1
3 M 0 1
4 F 0 1
5 F 0 1
6 F 0 1
7
First of all your construction of ABC leads to a structure with 3 factor
variables due to the way cbind processes the input variables - which is
not intended I think.
You can do sth like
ABC-data.frame(A,B,C)
aggregate(ABC[,2:3],by=list(A),sum)
hth.
Birgitle schrieb:
Hello R-Users!
I
Thanks for your answer.
It is intended, that the variables are treated as class factor, because
these are binary variables with, for example, the presence or the absence of
a plant organ.
As far as I understood, I have to treat them for other calculations as
factor. Therefore I classified these
Ok, then treat them as factors - but if they are really binary and coded
0 and 1, which kind of calculation would lead to different results for a
factor instead of a numeric variable?
Anyway,
ABC-as.data.frame(cbind(A,B,C))
aggregate(ABC[,2:3],by=list(A),FUN=function(x)sum(x=='1')) # '1' is
I think it makes a difference if I want to use a classification method like
rpart () or if I use a modelling approach like glm().
Many thanks for the kind and fast help. I am still very untrained and it is
difficult for me to create such codes.
B.
Eik Vettorazzi wrote:
Ok, then treat them
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