Controlling false discovery rates in factorial experiments with between-subjects and within-subjects tests
The False Discovery Rate (FDR) controls the expected number of false positives among the positive test results. It is not straightforward how to conduct a FDR controlling procedure in experiments with a factorial structure, while at the same time there are between-subjects and within-subjects factor...
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| Published in | BMC research notes Vol. 6; no. 1; p. 204 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
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England
BioMed Central Ltd
21.05.2013
BioMed Central |
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| Abstract | The False Discovery Rate (FDR) controls the expected number of false positives among the positive test results. It is not straightforward how to conduct a FDR controlling procedure in experiments with a factorial structure, while at the same time there are between-subjects and within-subjects factors. This is because there are P-values for different tests in one and the same response along with P-values for the same test and different responses.
We propose a procedure resulting in a single P-value per response, calculated over the tests of all the factorial effects. FDR control can then be based on the set of single P-values.
The proposed procedure is very easy to apply and is recommended for all designs with factors applied at different levels of the randomization, such as cross-over designs with added between-subjects factors.
NCT00959790. |
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| AbstractList | The False Discovery Rate (FDR) controls the expected number of false positives among the positive test results. It is not straightforward how to conduct a FDR controlling procedure in experiments with a factorial structure, while at the same time there are between-subjects and within-subjects factors. This is because there are P-values for different tests in one and the same response along with P-values for the same test and different responses.
We propose a procedure resulting in a single P-value per response, calculated over the tests of all the factorial effects. FDR control can then be based on the set of single P-values.
The proposed procedure is very easy to apply and is recommended for all designs with factors applied at different levels of the randomization, such as cross-over designs with added between-subjects factors.
NCT00959790. Doc number: 204 Abstract Background: The False Discovery Rate (FDR) controls the expected number of false positives among the positive test results. It is not straightforward how to conduct a FDR controlling procedure in experiments with a factorial structure, while at the same time there are between-subjects and within-subjects factors. This is because there are P -values for different tests in one and the same response along with P -values for the same test and different responses. Findings: We propose a procedure resulting in a single P -value per response, calculated over the tests of all the factorial effects. FDR control can then be based on the set of single P -values. Conclusions: The proposed procedure is very easy to apply and is recommended for all designs with factors applied at different levels of the randomization, such as cross-over designs with added between-subjects factors. Trial registration: NCT00959790 The False Discovery Rate (FDR) controls the expected number of false positives among the positive test results. It is not straightforward how to conduct a FDR controlling procedure in experiments with a factorial structure, while at the same time there are between-subjects and within-subjects factors. This is because there are P-values for different tests in one and the same response along with P-values for the same test and different responses. We propose a procedure resulting in a single P-value per response, calculated over the tests of all the factorial effects. FDR control can then be based on the set of single P-values. The proposed procedure is very easy to apply and is recommended for all designs with factors applied at different levels of the randomization, such as cross-over designs with added between-subjects factors. The False Discovery Rate (FDR) controls the expected number of false positives among the positive test results. It is not straightforward how to conduct a FDR controlling procedure in experiments with a factorial structure, while at the same time there are between-subjects and within-subjects factors. This is because there are P-values for different tests in one and the same response along with P-values for the same test and different responses.BACKGROUNDThe False Discovery Rate (FDR) controls the expected number of false positives among the positive test results. It is not straightforward how to conduct a FDR controlling procedure in experiments with a factorial structure, while at the same time there are between-subjects and within-subjects factors. This is because there are P-values for different tests in one and the same response along with P-values for the same test and different responses.We propose a procedure resulting in a single P-value per response, calculated over the tests of all the factorial effects. FDR control can then be based on the set of single P-values.FINDINGSWe propose a procedure resulting in a single P-value per response, calculated over the tests of all the factorial effects. FDR control can then be based on the set of single P-values.The proposed procedure is very easy to apply and is recommended for all designs with factors applied at different levels of the randomization, such as cross-over designs with added between-subjects factors.CONCLUSIONSThe proposed procedure is very easy to apply and is recommended for all designs with factors applied at different levels of the randomization, such as cross-over designs with added between-subjects factors.NCT00959790.TRIAL REGISTRATIONNCT00959790. Background The False Discovery Rate (FDR) controls the expected number of false positives among the positive test results. It is not straightforward how to conduct a FDR controlling procedure in experiments with a factorial structure, while at the same time there are between-subjects and within-subjects factors. This is because there are P-values for different tests in one and the same response along with P-values for the same test and different responses. Findings We propose a procedure resulting in a single P-value per response, calculated over the tests of all the factorial effects. FDR control can then be based on the set of single P-values. Conclusions The proposed procedure is very easy to apply and is recommended for all designs with factors applied at different levels of the randomization, such as cross-over designs with added between-subjects factors. Trial registration NCT00959790 Keywords: Analysis of variance, Between-subjects effects, Factorial experiment, False discovery rate, Within-subjects effects BACKGROUND: The False Discovery Rate (FDR) controls the expected number of false positives among the positive test results. It is not straightforward how to conduct a FDR controlling procedure in experiments with a factorial structure, while at the same time there are between-subjects and within-subjects factors. This is because there are P-values for different tests in one and the same response along with P-values for the same test and different responses. FINDINGS: We propose a procedure resulting in a single P-value per response, calculated over the tests of all the factorial effects. FDR control can then be based on the set of single P-values. CONCLUSIONS: The proposed procedure is very easy to apply and is recommended for all designs with factors applied at different levels of the randomization, such as cross-over designs with added between-subjects factors. TRIAL REGISTRATION: NCT00959790 |
| ArticleNumber | 204 |
| Audience | Academic |
| Author | Rubingh, Carina M Wopereis, Suzan van Erk, Marjan Schoen, Eric D |
| AuthorAffiliation | 1 TNO Earth, Environmental and Life Sciences, PO Box 360, 3700 AJ Zeist, Netherlands 2 Department of Environment, Technology and Technology Management, University of Antwerp, Prinsstraat 13, 2000 Antwerp, Belgium |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/23693065$$D View this record in MEDLINE/PubMed |
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| Copyright | COPYRIGHT 2013 BioMed Central Ltd. 2013 Schoen et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License(http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Copyright © 2013 Schoen et al.; licensee BioMed Central Ltd. 2013 Schoen et al.; licensee BioMed Central Ltd. |
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| References | SW Greenhouse (2248_CR4) 1959; 24 RA Fisher (2248_CR7) 1935 JD Storey (2248_CR3) 2003; 100 RA Bailey (2248_CR6) 2008 Y Benjamini (2248_CR2) 1995; 57 Y Fang (2248_CR8) 2008 Y Hochberg (2248_CR1) 1987 RA McLean (2248_CR5) 1991; 45 Y Benjamini (2248_CR9) 2001; 29 12883005 - Proc Natl Acad Sci U S A. 2003 Aug 5;100(16):9440-5 |
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| Snippet | The False Discovery Rate (FDR) controls the expected number of false positives among the positive test results. It is not straightforward how to conduct a FDR... Background The False Discovery Rate (FDR) controls the expected number of false positives among the positive test results. It is not straightforward how to... Doc number: 204 Abstract Background: The False Discovery Rate (FDR) controls the expected number of false positives among the positive test results. It is not... BACKGROUND: The False Discovery Rate (FDR) controls the expected number of false positives among the positive test results. It is not straightforward how to... |
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| SubjectTerms | Analysis Analysis of Variance Body mass index Diet Expected values Factorial experiment designs False Positive Reactions Medical research Medicine, Experimental Methods Studies Technical Note Variables |
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| Title | Controlling false discovery rates in factorial experiments with between-subjects and within-subjects tests |
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