From: Tavpritesh <tavpritesh_at_gmail.com>

Date: Sun, 24 Jun 2007 14:27:32 -0700 (PDT)

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Date: Sun, 24 Jun 2007 14:27:32 -0700 (PDT)

Hi Mike,

Thanks for the help, but I want to conduct tests, not between column 1 & 2
of the data but between the values of column two itself which have been
categorized into 3 classes, and indexed in column 1 as 1,2 and 3. Also if
you could help me with the commands for ANOVA for the same purpose, for
three classes.

Thanks.

Mike Meredith wrote:

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**>
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> You can investigate what's gone wrong after the loop has failed by looking

*> at the values of i, k, p, and t. Although d[(d[,(i+1)]%in%1),1] produces a
**> vector, k has only one element. Same with p. Should then be obvious why
**> the t.test produces an error.
**>
**> The problem is with the [i] index for k and p; take those away and it
**> works. If you want to keep the values generated in the loop, make k and p
**> lists and index with k[[i]] and p[[i]].
**>
**>
**> A better way to do this would be to use 'sample' to randomize the measured
**> values in d[,1] and then use d[,2] to group them for testing. You can then
**> use hundreds of iterations:
**>
**> t <- rep(NA, 999)
**> for(i in 1:999) {
**> samp <- sample(d[,1])
**> t <- t.test(samp[d[,2]==1], samp[d[,2]==2])$p.value
**> }
**> sum(t < 0.05) # How many were 'significant'?
**>
**> Note that I prefer to use t <- rep(NA,...) to allocate space, rather than
**> 1:999, so that NA appears as the result if there's a problem.
**>
**> Why not just do a randomization test?
**>
**> t <- rep(NA, 1000)
**> t[1] <- mean(d[d[,2]==1,1]) - mean(d[d[,2]==2,1]) # This is the observed
**> difference in means
**> for(i in 2:1000) {
**> samp <- sample(d[,1])
**> t[i] <- mean(samp[d[,2]==1]) - mean(samp[d[,2]==2])
**> }
**> t <- abs(t) # Skip this line if you want a 1-sided test
**> sum(t >= t[1])/1000 # This is the 'p-value'
**>
**> HTH, Mike.
**>
**>
**> Tavpritesh Sethi wrote:
*

>> >> hi all, >> I have a matrix with first column having some measurable values, these >> are >> indexed by the numerals 1,2 and 3 in the other columns of the data and >> may >> be interpreted as values for categories 1,2 and 3. >> I have written the following loop >> t<-1:10 >> for(i in 1:10) >> + { >> + k[i]<-d[(d[,(i+1)]%in%1),1] >> + p[i]<-d[(d[,(i+1)]%in%2),1] >> + t[i]<-t.test(k[i],p[i])$p.value >> + } >> Error in t.test.default(k[i], p[i]) : not enough 'x' observations >> In addition: Warning messages: >> 1: number of items to replace is not a multiple of replacement length >> 2: number of items to replace is not a multiple of replacement length >> >> As you might have understood, I want to test for difference between the >> two >> cagories: "k" and "v". the second column of the data is the original >> categorization and the rest columns(3:10) are a matrix of randomized >> values >> between 1 to 3. (I have three categories) >> My purpose of doing so is to check whether significant difference comes >> up >> in the randomized data also. This is to check the effect of the small >> sample >> size of my data. >> Please suggest a way or an alternative to the above approach. >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> R-help_at_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 >> and provide commented, minimal, self-contained, reproducible code. >> >>

-- View this message in context: http://www.nabble.com/warning-in-a-loop-tf3969850.html#a11278677 Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help_at_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 and provide commented, minimal, self-contained, reproducible code.Received on Sun 24 Jun 2007 - 21:35:26 GMT

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