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.
