Chi-square yields an unadjusted odds ratio with 95% confidence interval
The width of the confidence interval is entirely dependent upon the sample size. The confidence interval is the best inference that can be derived from chi-square analysis. Larger samples will yield more precise and accurate measures of effect. Smaller samples will generate wider confidence intervals. Fisher's Exact test is employed instead of chi-square when there are less than 5 observations in any of the four cells of the 2x2 table or with sample sizes of less than 20 participants (n = 20).
Odds ratios higher than 1.0 that have a confidence interval that does not cross over 1.0 can be interpreted as meaning that the outcome is that many more times likely to occur versus the comparison group.
Odds ratios that are lower than 1.0 and have confidence intervals that cross over 1.0 are considered "protective effects," meaning that the outcome is less likely to occur versus the comparison group.
1. What are the odds of exposure versus non-exposure causing the outcome?
2. What are the odds of non-exposure versus exposure causing the outcome?
3. What are the odds of exposure versus non-exposure NOT causing the outcome?
4. What are the odds of non-exposure versus exposure NOT causing the outcome?
So, when structuring your 2x2 table for unadjusted odds ratios, make sure that you have the data set up to answer your research question by having it located in Cell A of the table.
The steps for conducting a Chi-square 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 a Chi-square
2. Interpret the Pearson Chi-Square 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.
When to use Fisher's Exact Test rather than Chi-square
Click on the Fisher's Exact Test button if there is a violation of the above assumption or there are less than 20 observations.
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