Hi Bert, Thanks for your reply. If I understand correctly, prop.test() is not suitable to my situation. The input to prop.test() is 2 numbers for each group (# of success and # of trials, for example, groups 1 has 5 success out of 10 trials; group 2 has 3 success out of 7 trials; etc. prop.test() tests whether the probability of success is the same across groups.
In my case, each group has several subjects and each subject has 2 numbers (# success and # trials). So for group 1: subject 1: 5 success, 10 trials subject 2: 3 success, 8 trials : : for group 2: subject a: 7 success, 9 trials subject b: 6 success, 7 trials : : I want to test whether the probability of success in group 1 is the same as in group 2. It's like comparing 2 groups of samples using t test, what I am uncertain about is that whether regular t test (or non-pamametric test) is still appropriate here when the response variable is actually proportions. I guess prop.test() can not be used with my dataset, or I may be wrong? Thanks John ________________________________ From: Bert Gunter <gunter.ber...@gene.com> Sent: Wed, February 9, 2011 3:58:05 PM Subject: Re: [R] comparing proportions 1. Is this a homework problem? 2. ?prop.test 3. If you haven't done so already, get and consult a basic statistical methods book to help you with questions such as this. -- Bert > Hi, I have a dataset that has 2 groups of samples. For each sample, then > response measured is the number of success (no.success) obatined with the >number > of trials (no.trials). So a porportion of success (prpop.success) can be > computed as no.success/no.trials. Now the objective is to test if there is a > statistical significant difference in the proportion of success between the 2 > groups of samples (say n1=20, n2=30). > > I can think of 2 ways to do the test: > > 1. regular t test based on the variable prop.success > 2. Mann-Whitney test based on the variable prop.success > 2. do a binomial regression as: > fit<-glm(cbind(no.success,no.trials-no.success) ~ group, data=data, > family=binomial) > anova(fit, test='Chisq') > > My questions is: > 1. Is t test appropriate for comparing 2 groups of proportions? > 2. how about Mann-Whitney non-parametric test? > 3. Among the 3, which technique is more appropriate? > 4. any other technique you can suggest? > > Thank you, > > John > > > > [[alternative HTML version deleted]] > > > ______________________________________________ > R-help@r-project.org 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. > > -- Bert Gunter Genentech Nonclinical Biostatistics [[alternative HTML version deleted]]
______________________________________________ R-help@r-project.org 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.
