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How to Report Cohen’s d in APA Style

Effect sizes are essential in scientific research for understanding the practical significance of study findings.

While statistical significance provides valuable information about the likelihood that a result is due to chance, it is crucial to consider the magnitude of the observed effects to better interpret research outcomes.

One widely-used measure of effect size is Cohen’s d, which quantifies the standardized mean difference between two groups.

This article will discuss the importance of reporting effect sizes in psychological research, focusing on Cohen’s d and how to report it following the American Psychological Association (APA) format.

What is Cohen's d?

Cohen’s d is a standardized effect size measure to quantify the difference between two group means.

It is calculated by dividing the difference between the means of two groups by the pooled standard deviation.

Cohen’s d is beneficial for comparing effect sizes across studies with different sample sizes or scales, as it eliminates the units of measurement.

The resulting dimensionless value represents the difference between the two groups regarding standard deviations.

In terms of interpretation, Cohen’s d values can be considered as small (0.2), medium (0.5), or large (0.8) effect sizes.

However, these thresholds are merely guidelines and may vary depending on the research context.

Cohen's d Effect size
0.00-0.19
Very small
0.20-0.49
Small
0.50-0.79
Medium
0.80+
Large

Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates.

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How to Report Cohen's d in APA Format?

When reporting Cohen’s d in APA format, follow these steps to ensure clarity and proper formatting:

1. Mention Cohen’s d: Clearly state that you are reporting Cohen’s d as a measure of effect size.

2. Use appropriate notation: Represent Cohen’s d with a lowercase “d” followed by an equal sign and the calculated value.

3. Round to two decimal places: Round the value of Cohen’s d to two decimal places for consistency with other statistical values reported in APA style.

4. Provide context: Offer an interpretation of the effect size based on the context of your study and the conventions for interpreting Cohen’s d (e.g., small = 0.2, medium = 0.5, large = 0.8).

Example

The independent samples t-test revealed a significant difference in test scores between Group A (M = 75.23, SD = 9.42) and Group B (M = 80.15, SD = 8.63), t(48) = -2.16, p = .035. The effect size, as measured by Cohen’s d, was d = 0.62, indicating a medium effect.

In this example, the reported Cohen’s d value helps readers understand the magnitude of the difference between the two groups beyond the significance level.

How to Report t-test in APA Style?

Want to learn more? Check out our related content.

Calculating Cohen's d

Cohen’s d = (M1 – M2) / SD_pooled

where M1 and M2 are the means of the two groups, and SD_pooled is the pooled standard deviation, calculated as:

SD_pooled = √[((n1 – 1) * SD1² + (n2 – 1) * SD2²) / (n1 + n2 – 2)]

where n1 and n2 are the sample sizes of the two groups, and SD1 and SD2 are their respective standard deviations.

Conclusion

Incorporating effect sizes like Cohen’s d into your research reporting is vital for comprehensively understanding your study’s findings.

Following the APA format for reporting statistical results, including Cohen’s d, ensures consistency, clarity, and accurate interpretation of your research outcomes.

By adequately reporting effect sizes, you enhance the readability of your research and contribute to the broader scientific community’s ability to synthesize and compare findings across studies.

As you continue to engage in psychological research, remember to use measures like Cohen’s d to convey the practical significance of your results and adhere to APA guidelines for clear, concise, and meaningful communication of your findings.

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