We can address the limitations of the chi-square test by calculating Cramér's V, which quantifies the strength of the association between categorical variables. This value ranges from 0 to 1, with higher values indicating a stronger relationship. By using Cramér's V, we gain additional insight into the practical significance of the results, helping to interpret the data beyond just determining whether an association exists.
Kishore K, Jaswal V. Statistics corner: Chi-squared test. J Postgrad Med Educ Res. 2023 Apr 10;57(1):40-4.
To address the limitations of the chi-square test using Cramér's V:
1. Calculate Cramér's V after conducting the chi-square test.
2. Use Cramér's V to measure the effect size (strength of association).
3. Interpret Cramér's V values:
- Small: 0.00-0.10
- Medium: 0.10-0.30
- Large: 0.30-0.50
- Very large: 0.50-1.00
Cramér's V helps overcome chi-square test limitations by:
1. Providing effect size measurement
2. Reducing sensitivity to sample size
3. Offering intuitive interpretation
This enhances your statistical analysis and provides a more comprehensive understanding of your data.
To add a further limitation, it does not give the direction of the association (positive vs negative) for this reason Chi-Square + Cramer V falls second to logistic regression.
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