Hi Jorge,
> apply(mydata[,-1], 2, tapply, mydata[,1], function(x)
sum(x)/nrow(mydata))
will calculate the total percentages of "yes" for each sex relative to
the total size, not within sex.
with your data construction, the following should work
#count "yes" for each sex and question
cnts<-aggregate(mydata[,-1],by=list(mydata[,1]),FUN=sum)
#count gender as denumerators
nums<-table(mydata[,1])
cbind(sex=cnts[,1],cnts[,-1]/nums)
#simple check that the solution is ok
prop.table(table(sex=mydata[,"sex"],q1=mydata[,"q1"]),1)
prop.table(table(sex=mydata[,"sex"],q2=mydata[,"q2"]),1)
Jorge Ivan Velez schrieb:
Dear Donald,
Assuming that your data is called "mydata", the first column represents the
gender and the questions are the columns left, something like the following
should do the job:
# Some data
set.seed(1)
mydata <- matrix(rbinom(1000,1,p=0.5),ncol=10)
colnames(mydata)<-c('sex',paste('q',1:9,sep=""))
# What you asked -- hopefully ;)
apply(mydata[,-1], 2, tapply, mydata[,1], function(x) sum(x)/nrow(mydata))
HTH,
Jorge
On Tue, Apr 7, 2009 at 4:33 PM, Donald Braman <dbra...@law.gwu.edu> wrote:
I've been playing around with various table tools, trying to construct a
fairly simple cross-tab. It shouldn't be hard, but for some reason it
turning out to be (for me).
If I want to see how many men and how many women agree with a
agree/disagree
question (coded 1,0), I can do this:
attach(mydata)
mytable <- table(male, q1.bin) # gender and a binary response variable
prop.table(mytable, 1) # row percentages
q1.bin
male 0 1
0 0.3988 0.6012
1 0.2879 0.7121
I can repeat that for each of the items I want gender breakdowns for (q2,
q3, q4 ....). But what I really want is a table that shows the percentage
answering yes (coded as 1) across many, many binary response items. E.g.,
male q1.bin q2.bin q3.bin ...
0 0.6012 0.3421 0.9871 ...
1 0.7121 0.6223 0.0198 ...
I've tried various combinations of apply & cbind, but to no avail. It would
be easy in SPSS crosstabs, but darnit, I want to use R!
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