I think that I can answer my own question, which was which R function is
appropriate for the test I need. It looks like the EMT package and the exact
multinomial test is appropriate for goodness-of-fit to test a null
hypothesis of equal proportions, given at least 3 categories. Unless I am
wrong, I
Thank you David, Peter, and Peter,
I understand now that I would be misusing fisher.test to use it for a
goodness-of-fit test and that non-integer data are inappropriate since it is
for testing two sets of observed counts.
Peter D., it does not seem like a good idea for me to "cheat" fisher.test
David,
Thanks for your reply--I appreciate your thoughts. I will look at prop.test.
The reason I chose fisher.test over chisq.test is that fisher.test is more
appropriate when observed counts are not numerous--empty cells and cells
with counts < 5 are less a problem.
Expected values are needed
I seem to be able to use expected values that are decimal (e.g., 1.33) when
using chisq.test but not when using fisher.test. This happens when using an
array/matrix as input. Fisher.test returns: Error in sprintf(gettext(fmt,
domain = domain), ...) : invalid format '%d'; use format %s for character
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