Benjamini-Hochberg Procedure

Definition

The Benjamini-Hochberg Procedure is a method used to control the false discovery rate (FDR) when conducting multiple hypothesis tests. This procedure helps researchers identify significant results while minimizing the chances of falsely declaring a discovery, making it particularly valuable in fields with high-dimensional data, like genomics. By ranking p-values and applying a specific threshold based on their rank and the total number of tests, this approach allows for a more balanced assessment of significance across multiple tests.

5 Must Know Facts For Your Next Test

1. The Benjamini-Hochberg Procedure was introduced in 1995 by Yoav Benjamini and Daniel Yekutieli as a way to control the false discovery rate.
2. This procedure is particularly useful in scenarios where many hypotheses are being tested simultaneously, such as in gene expression studies.
3. The method works by sorting p-values from smallest to largest and comparing each to its corresponding threshold based on its rank and the total number of tests.
4. Unlike methods that control family-wise error rates, the Benjamini-Hochberg Procedure is generally less conservative, allowing for more discoveries while managing false positives.
5. Researchers can use this procedure to make decisions about which hypotheses to reject while maintaining an acceptable level of false discoveries.

Review Questions

• How does the Benjamini-Hochberg Procedure help researchers balance discovery and error rates in multiple hypothesis testing?
  • The Benjamini-Hochberg Procedure helps researchers balance discovery and error rates by controlling the false discovery rate (FDR) rather than the family-wise error rate (FWER). By ranking p-values and applying a threshold based on their ranks, this method allows for identifying significant results while minimizing false positives. This approach is particularly beneficial in high-dimensional settings where numerous tests are conducted simultaneously.
• In what scenarios would the Benjamini-Hochberg Procedure be preferred over traditional methods that control family-wise error rates?
  • The Benjamini-Hochberg Procedure is preferred over traditional methods that control family-wise error rates in scenarios where researchers are willing to tolerate some level of false discoveries in exchange for identifying more true positives. This is especially true in fields like genomics or neuroimaging, where thousands of hypotheses are tested concurrently. The less conservative nature of this procedure allows researchers to detect potentially significant findings that might be missed if strict family-wise error rate controls were applied.
• Evaluate the impact of using the Benjamini-Hochberg Procedure on research outcomes in fields with high-dimensional data analysis.
  • Using the Benjamini-Hochberg Procedure can significantly impact research outcomes in fields with high-dimensional data analysis by enabling researchers to identify more meaningful discoveries without being overly stringent about error rates. This method fosters an environment where important trends and patterns can be detected that might otherwise remain hidden due to conservative testing methods. However, while it enhances discovery potential, it also requires researchers to be vigilant about interpreting findings within the context of FDR, ensuring that reported discoveries are reliable and contribute valuable insights to the field.

Related terms

False Discovery Rate: The expected proportion of false discoveries among the rejected hypotheses, serving as a critical measure in multiple hypothesis testing.

P-value: A measure that indicates the strength of evidence against the null hypothesis; lower p-values suggest stronger evidence for rejecting the null hypothesis.

Multiple Testing: The process of conducting several statistical tests simultaneously, which increases the risk of Type I errors without appropriate adjustments.