# Interpreting infinite odds ratio and confidence interval from Fisher's test

Cross Validated Asked on November 29, 2020

I’ve performed a two-sided Fisher’s exact test on the following data, and the results include Infinity for the upper confidence interval and odds ratio. Are these results erroneous, and if not how do I interpret them? I’ve done a bunch of searching and reading, but have a hard time wrapping my head around why the infinite results occur. When I add 0.5 to each cell I still obtain infinity.

Data:

    Fisher's Exact Test for Count Data

p-value = 0.002719
alternative hypothesis: true odds ratio is not equal to 1
95 percent confidence interval:
2.196186      Inf
sample estimates:
odds ratio
Inf


Any insight is greatly appreciated

The issue is not the results of Fisher's test - as Frank Harrell pointed out, you are dividing by 0.

The results are fine, I think it's the question that needs work. That is, rather than ask about the odds ratio, you might want to ask about something else, like a test of proportions. This topic has an extensive literature.

Are the results variable? Well, not from this sample, but you might, of course, get different values in a different sample. You might get a 1 instead of a 0 for the upper right cell.

Answered by Peter Flom on November 29, 2020

Knowing the formula to calculate the odds ratio will tell you why you get an 'Inf' value. Basically, you're dividing by 0. There's a lot of documentation available on the net (here you can find an example).

As to adding 0.5 to all values, the R implementation of the Fisher's Test only works with nonnegative integers. Even if you add 0.5, the values will be rounded to integers (so 0.5 will become 0).

Answered by Daniel A on November 29, 2020

## Related Questions

### Compare the results of two canonical correlation analyses (CCA)

1  Asked on February 18, 2021 by forlooper

### Why doesn’t the optimizer just look for stationary points of the loss function?

1  Asked on February 18, 2021 by borut-flis

### Statistical analysis for comparing expertise levels between 3 groups

0  Asked on February 17, 2021 by kaaren0111

### Find the prior distribution for the natural parameter of an exponential family

1  Asked on February 17, 2021 by xxtensionxx

### Using decision tree for unsupervised discretization?

1  Asked on February 17, 2021 by aflatoun

### How to conduct a multilevel model/regression for panel data in Python?

1  Asked on February 17, 2021 by exlo

### How to choose resample size when drawing without replacement?

1  Asked on February 17, 2021

### Two-way repeated measures ANOVA vs mixed ANOVA

1  Asked on February 16, 2021 by xe-m

### What is the adjusted R-squared formula in lm in R and how should it be interpreted?

2  Asked on February 16, 2021 by user1272262

### Linear model selection – Subset, Forward

0  Asked on February 16, 2021 by davud-mursalov

### What model to use for analyzing age frequency data? issues with linear model in R

1  Asked on February 16, 2021 by johnny5ish

### Dimensionality reduction of a large covariance matrix

0  Asked on February 15, 2021 by wilmer-e-henao

### How to estimate variance of classifier on test set?

2  Asked on February 15, 2021 by pterojacktyl

### Churn prediction for customers with limited data

0  Asked on February 14, 2021 by ahmet-turul-bayrak

### multiple linear regression vs polynomial regression models

0  Asked on February 14, 2021 by gracetam

### Multiple Regression study design – questionnaires

1  Asked on February 14, 2021

### Which package works for mediation analysis in R when variables are categorical?

0  Asked on February 14, 2021 by fouzia-farooq

### Compare two samples with many zeros

4  Asked on February 14, 2021

### Non-statistically significant effect of the instrument in the reduced form of the 2SLS

1  Asked on February 14, 2021 by fuca26

### What are the different types of averages?

4  Asked on February 14, 2021 by gpuguy