One of the main challenges in subgroup analysis is the risk of false positives. When multiple subgroups are analyzed, the likelihood of finding a statistically significant result by chance increases. This is known as the multiple comparisons problem. To address this, researchers often use statistical adjustments like the Bonferroni correction or False Discovery Rate (FDR) control.
Another challenge is sample size. Subgroup analyses often involve smaller sample sizes, which can lead to reduced statistical power and increased variability. This makes it harder to detect true differences and increases the risk of type II errors (failing to detect a true effect).
