Sam Wiebe writes:
>I would appreciate comments on how to deal with empty cells
>in 2 by n tables when calculating Likelihood ratios. For
>example, adding 0.5 or 0.1 to each cell produces enormously
>different likelihood ratios. Thanks in advance.
I'm not an expert in likelihood ratios, but since nobody else answered.
An empty cell means that your likelihood ratio is either zero or infinity.
If that were really true, you would have a pretty darn good test. But you
and I both know that the true likelihood ratio is never going to be that
extreme. The empty cell is caused by sampling error, and ideally, you would
account for that sampling error by using confidence limits for your
likelihood ratio. In fact, you should use confidence intervals even when you
don't have an empty cell, but that's another story.
There are some formulas that you could use yourself for confidence limits
for a likelihood ratio, but they don't work when you have empty cells. The
methods that do work require sophisticated statistical software.
The only practical suggestion I would have is to pool adjacent categories so
that you have enough data to estimate a stable likelihood ratio.
Another possibility is to decide in advance what sort of likelihood ratio
you want to have and then add whatever constant gives you that desired
likelihood ratio. <grin>
Steve Simon, [log in to unmask], Standard Disclaimer.
Ask Professor Mean: http://www.cmh.edu/stats/profmean.htm
<http://www.cmh.edu/stats/profmean.htm>
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