HI,
Try this:
n<-100
dat1<-data.frame(hunting.prev=sample(c("success","fail"),n,
replace=TRUE),groupsize=sample(c("small","large"),n,replace=TRUE),dogs=sample(c("yes","no"),n,replace=TRUE),
guns=sample(c("yes","no"),n,replace=TRUE))
mytable<-xtabs(~hunting.prev+groupsize+dogs+guns,data=dat1)
ftable(mytable)
guns no yes
hunting.prev groupsize dogs
fail large no 5 10
yes 3 9
small no 8 7
yes 6 2
success large no 10 3
yes 7 10
small no 7 6
yes 6 1
summary(mytable)
#Call: xtabs(formula = ~hunting.prev + groupsize + dogs + guns, data = dat1)
#Number of cases in table: 100
#Number of factors: 4
#Test for independence of all factors:
# Chisq = 16.749, df = 11, p-value = 0.1155
# Chi-squared approximation may be incorrect
A.K.
----- Original Message -----
From: Sacha Viquerat <dawa.ya.m...@googlemail.com>
To: "r-help@r-project.org" <r-help@r-project.org>
Cc:
Sent: Friday, August 10, 2012 6:48 AM
Subject: [R] creating a contingency table from a data.frame automatically (NOT
BY HAND)
Hello there!
I am still struggling with a binomial response over all categorical variables
(some of them with 3 levels, most with 2 levels). After initial struggles with
glm's (struggle coming from the data, not the actual analysis) I have decided
to prefer contingency tables. I have my data such as:
response:
hunting.prev=c("success","fail","success","success","success","fail",...)
one of 21 surveyed variables:
groupsize=c("small","large","small","small","small","large"...)
...
now...
It is intuitive to me that I will have to split up each variable by its
level(s), thus creating 2 new variables for groupsize (as an example) holding
the counts of small hunting parties when the hunting.prev was a success and so
on. I could write a function to do that for me, however, never intend to
reinvent the wheel. I would like my data to look like that:
hunting prev groupsize-small groupsize-large dogs-yes dogs-no
guns-yes guns-no...
success 12 2 4 14 23 12...
failure 1 6 34 0 12 3...
of course, hunting.prev would only be needed to create the index via
hunting.prev=="success" and is here used to indicate what each row means. My
questions would be:
a) how to count and split each categorical variable by a response variable, how
to create a 2x20something (contingency) table and how far a prop.test()
approach or a chi² may be more appropriate to actually analyze the data.
b) how do you guys create R output so that it's formatted in nice columns and
rows?
Hope to see help,
Thanks!
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______________________________________________
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
