# fisher's exact test with values less than 1

I have a rxc contingency table that has values that are less than 1.

For Example:

        satisfication
income  VeryD LittleD
< 15k  2e-03  0.0057
15-25k 8e-04  0.0013
25-40k 1e-03  0.0010
> 40k  4e-03  0.0237


Error in fisher.test(Job) : FEXACT error 3. All elements of TABLE are zero. PRT and PRE are set to missing values. In addition: Warning message: In fisher.test(Job) : 'x' has been rounded to integer: Mean relative difference: 1

Is there something I can do to get around this error? I am not using counts but data that is normalized to account for volume.

• What are veryD and LittleD? Nov 5, 2018 at 20:41
• Use the counts.
– whuber
Nov 5, 2018 at 21:33
• You can't "normalize to account for volume" and get a correct test. If you need to have some exposure measure included in the model, could (perhaps) look at a Poisson GLM with an offset. Nov 6, 2018 at 7:12