I don't have a good reference for you, but here are a couple of things that you could try:
1. Do a bootstrap estimation of p by resampling the blocks of 5 (rather than the individual observations) and see if the hypothesized p is in the confidence interval. 2. Simulate data using the hypothesized p and the blocking structure that was actually used (find the amount of random error to add to the base p for each block that gives the desired ICC) then compute the sample proportion from the simulated data. Redo this a bunch of times to get the sampling distribution of the sample proportion. Compare the sample proportion from the real data to this distribution to get a p-value. 3. Use the glmer function from lme4 with the responses as the left side of the formula and an intercept as the right side with the groups forming the random variable, then look at the inferences on the intercept and how it compares to the hypothesized p. (this one is probably overkill for this problem, but should work in theory). Hope this helps, -- Gregory (Greg) L. Snow Ph.D. Statistical Data Center Intermountain Healthcare [EMAIL PROTECTED] 801.408.8111 > -----Original Message----- > From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] > project.org] On Behalf Of Matthias Gondan > Sent: Tuesday, November 25, 2008 7:53 AM > To: [EMAIL PROTECTED] > Subject: [R] Statistical question: one-sample binomial test for > clustered data > > Dear list, > > I hope the topic is of sufficient interest, because it is not > R-related. I have N=100 yes/no-responses from a psychophysics > paradigm (say Y Yes and 100-Y No-Responses). I want to see > whether these yes-no-responses are in line with a model > predicting a certain amount p of yes-responses. Standard > procedure would be a one-sample binomial test for the observed > proportion, > > chi²(1 df) = (Y-Np)²/(Np) + [(100-Y)-N(1-p)]²/[N(1-p)] > > Actually, this is the approximate chi²-test, but the sample > size seems to be reasonably high for an asymptotic test. > > The problem is that the experiment took quite a while, and > the 100 responses are grouped into 20 blocks of 5 responses > each. The responses within the blocks are clustered, ICC is > about 0.13 or so. > > Can anyone point me to some literature explaining a one-sample > binomial test / or chi² test for correlated data? Most of the > literature I found starts with more advanced stuff, e.g. > 2x2 cross-tabulated data. > > Best wishes, > > Matthias > > ______________________________________________ > 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. ______________________________________________ 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.
