Multiple hypothesis testing in allergy and hypersensitivity diseases investigation: a pedagogical perspective

Abstract

Background

Allergy and hypersensitivity diseases (AHD) are multifactorial diseases affecting different organs of the human body and with different level of severity. Therefore, multiple hypothesis testing is a common practice in AHD investigation. However, this increases the probability of rejecting a true null hypothesis, meaning there's no effect, the so-called risk of type 1 error or alpha risk. We present here how to control global alpha risk in the case of multiple comparisons or multitesting in AHD investigations to minimize the risk of drawing false positive conclusions.

Methods

Four methods for controlling global alpha risk, namely Bonferroni, Sidak, Holm–Bonferroni, and Benjamini–Hochberg, were applied to simulated and real data. Their performance was assessed through false negative, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV).

Results

The Bonferroni method was found to be the most conservative, while the Benjamini–Hochberg method had the most power. The Holm–Bonferroni method was a compromise between statistical power and control of false positives.

Conclusions

Controlling global alpha risk is crucial in multiple comparisons like they are needed in AHD investigation, and different methods are available to achieve it. Researchers should choose the method that best suits their study, considering the assumptions and objectives.