A Complete Review of Controlling the FDR in a Multiple Comparison\n Problem Framework -- The Benjamini-Hochberg Algorithm
Anish Acharya
Abstract
Open-access reader
Anish Acharya
Abstract
Open-access reader
This paper is a review of the popular Benjamini Hochberg Method and other\nrelated useful methods of Multiple Hypothesis testing. This is written with the\npurpose of serving a short but complete easy to understand review of the main\narticle with proper background. The paper titled 'Controlling the False\nDiscovery Rate-a practical and powerful Approach to multiple Testing' by\nbenjamini et. al.[1] proposes a new framework of controlling the False\nDiscovery Rate in a Multiple Hypothesis testing problem. It has been claimed\nthat the procedure proposed in the paper results in a substantial gain in power\nmore applicable in case of problems which call for False discovery rate (FDR)\ncontrol rather than Familywise Error Rate (FWER). The proposed method uses a\nsimple Bonferroni type procedure for FDR control.\n
A significance statement is not available in the OpenAlex record.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
This paper is a review of the popular Benjamini Hochberg Method and other\nrelated useful methods of Multiple Hypothesis testing. This is written with the\npurpose of serving a short but complete easy to understand review of the main\narticle with proper background. The paper titled 'Controlling the False\nDiscovery Rate-a practical and powerful Approach to multiple Testing' by\nbenjamini et. al.[1] proposes a new framework of controlling the False\nDiscovery Rate in a Multiple Hypothesis testing problem. It has been claimed\nthat the procedure proposed in the paper results in a substantial gain in power\nmore applicable in case of problems which call for False discovery rate (FDR)\ncontrol rather than Familywise Error Rate (FWER). The proposed method uses a\nsimple Bonferroni type procedure for FDR control.\n
Key concepts: False discovery rate, Bonferroni correction, Multiple comparisons problem, Computer science, Algorithm, Word error rate, Control (management), Data mining