If I am following you, expectency counts below 5 usually means you should run an exact test (I.e., Fisher's exact test) . Though you have a very large overall sample size that may make the procedure pretty computationally heavy.
Hello,
I have been reading a little bit about structural zeros and chi-square goodness of fit tests.
I've not been able to find a clear answer as to whether 'structural zeros' are only relevant in the observed data... In other words, is it a violation of the assumptions of the chi-square to have 0 for an expected value?
Example:
x: 1929, 3283, 293, 2015
p: 0.2, 0.6, 0, 0.2
Where x are the observed counts and p the expected proportions.
Is that a legitimate test, or would I have to eliminate the 0, 293 value, ignoring the observed count for the unexpected variable?
Example:
x: 1929, 3283, 2015
p: 0.2, 0.6, 0.2
Thank you
If I am following you, expectency counts below 5 usually means you should run an exact test (I.e., Fisher's exact test) . Though you have a very large overall sample size that may make the procedure pretty computationally heavy.
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