If Bonferroni correction is applied, what happens to the likelihood of missing true effects?

If Bonferroni correction is applied, what happens to the likelihood of missing true effects?

• A. It decreases
• B. It increases
• C. It remains the same
• D. It becomes zero

Answer: (B)

When you apply a Bonferroni correction, you lower the significance threshold for each individual test to guard against false positives across many comparisons. That stricter threshold reduces the chance of declaring noise as a real effect, but it also makes it harder for true effects to reach significance. In other words, the study gains protection against Type I errors at the cost of more Type II errors. So, real, true effects—especially smaller ones—are more likely to be missed. This is the trade-off: stronger control of false positives leads to a higher chance of missing true effects.

When you apply a Bonferroni correction, you lower the significance threshold for each individual test to guard against false positives across many comparisons. That stricter threshold reduces the chance of declaring noise as a real effect, but it also makes it harder for true effects to reach significance. In other words, the study gains protection against Type I errors at the cost of more Type II errors. So, real, true effects—especially smaller ones—are more likely to be missed. This is the trade-off: stronger control of false positives leads to a higher chance of missing true effects.