structural zeros and chi square

wdmn

New Member
#1
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
 

hlsmith

Omega Contributor
#2
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.
 

wdmn

New Member
#3
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.
Thank you hlsmith.

I'm not sure I'm following you. An expectancy count below five would be (for example) 0.04 expected when the total sample size is 100? or 0 no matter what the sample size?