Fisher's Exact Test
Fisher's Exact test is used when the chi-square assumption is violated
Fisher's Exact Test is often used with small sample sizes (n < 20) and when researching rare outcomes. The p-value is not interpreted with Fisher's Exact Test. The unadjusted odds ratio with 95% confidence interval is used instead. The width of the 95% confidence interval will be extremely wide due to the limited number of observations in one of the four cells.
SPSS automatically calculates a Fisher's Exact Test p-value when conducting chi-square analysis.
The steps for conducting a Fisher's Exact Test in SPSS
2. Click Analyze.
3. Drag the cursor over the Descriptive Statistics drop-down menu.
4. Click Crosstabs.
5. Click on the dichotomous categorical predictor variable to highlight it.
6. Click on the arrow button to move the variable into the Row(s): box.
7. Click on the dichotomous categorical outcome variable to highlight it.
8. Click on the arrow button to move the variable into the Column(s): box.
9. Click on the Statistics button.
10. Click on the Chi-square box to select it.
11. Click on the Risk box to select it.
12. Click Continue.
13. Click OK.
The steps for interpreting the SPSS output for Fisher's Exact Test
2. Interpret the Fisher's Exact Test Exact Sig. (2-sided) p-value.
3. If researchers have a significant p-value, then they can interpret the first row in the Risk Estimate table. The unadjusted odds ratio is presented in the Value column and the lower and upper limits of the 95% confidence interval wrapped around the odds ratio.
If the p-value is significant and the odds ratio is above 1.0 along with the confidence interval, then the treatment group is MORE LIKELY to have the outcome.
If the p-value is significant and the odds ratio is below 1.0 along with the confidence interval, then the treatment group is LESS LIKELY to have the outcome.
If the p-value is non-significant, then researchers will see that the 95% confidence interval crosses over 1.0. They can report the odds ratio or p-value as needed.
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