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False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studies
by
Glickman, Mark E.
, Rao, Sowmya R.
, Schultz, Mark R.
in
Analysis. Health state
/ Biological and medical sciences
/ Biomedical Research - methods
/ Biomedical Research - standards
/ Biostatistics - methods
/ Data Interpretation, Statistical
/ Deepwater exploration & production
/ Economic models
/ Epidemiology
/ Error analysis
/ False discovery rate
/ False positive rate
/ False Positive Reactions
/ FWER
/ General aspects
/ Humans
/ Hypotheses
/ Internal Medicine
/ Medical research
/ Medical sciences
/ Multiple tests
/ P-value
/ Public health. Hygiene
/ Public health. Hygiene-occupational medicine
/ Randomized Controlled Trials as Topic - methods
/ Randomized Controlled Trials as Topic - psychology
/ Studies
/ Study-wide error rate
2014
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False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studies
by
Glickman, Mark E.
, Rao, Sowmya R.
, Schultz, Mark R.
in
Analysis. Health state
/ Biological and medical sciences
/ Biomedical Research - methods
/ Biomedical Research - standards
/ Biostatistics - methods
/ Data Interpretation, Statistical
/ Deepwater exploration & production
/ Economic models
/ Epidemiology
/ Error analysis
/ False discovery rate
/ False positive rate
/ False Positive Reactions
/ FWER
/ General aspects
/ Humans
/ Hypotheses
/ Internal Medicine
/ Medical research
/ Medical sciences
/ Multiple tests
/ P-value
/ Public health. Hygiene
/ Public health. Hygiene-occupational medicine
/ Randomized Controlled Trials as Topic - methods
/ Randomized Controlled Trials as Topic - psychology
/ Studies
/ Study-wide error rate
2014
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Do you wish to request the book?
False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studies
by
Glickman, Mark E.
, Rao, Sowmya R.
, Schultz, Mark R.
in
Analysis. Health state
/ Biological and medical sciences
/ Biomedical Research - methods
/ Biomedical Research - standards
/ Biostatistics - methods
/ Data Interpretation, Statistical
/ Deepwater exploration & production
/ Economic models
/ Epidemiology
/ Error analysis
/ False discovery rate
/ False positive rate
/ False Positive Reactions
/ FWER
/ General aspects
/ Humans
/ Hypotheses
/ Internal Medicine
/ Medical research
/ Medical sciences
/ Multiple tests
/ P-value
/ Public health. Hygiene
/ Public health. Hygiene-occupational medicine
/ Randomized Controlled Trials as Topic - methods
/ Randomized Controlled Trials as Topic - psychology
/ Studies
/ Study-wide error rate
2014
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False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studies
Journal Article
False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studies
2014
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Overview
Procedures for controlling the false positive rate when performing many hypothesis tests are commonplace in health and medical studies. Such procedures, most notably the Bonferroni adjustment, suffer from the problem that error rate control cannot be localized to individual tests, and that these procedures do not distinguish between exploratory and/or data-driven testing vs. hypothesis-driven testing. Instead, procedures derived from limiting false discovery rates may be a more appealing method to control error rates in multiple tests.
Controlling the false positive rate can lead to philosophical inconsistencies that can negatively impact the practice of reporting statistically significant findings. We demonstrate that the false discovery rate approach can overcome these inconsistencies and illustrate its benefit through an application to two recent health studies.
The false discovery rate approach is more powerful than methods like the Bonferroni procedure that control false positive rates. Controlling the false discovery rate in a study that arguably consisted of scientifically driven hypotheses found nearly as many significant results as without any adjustment, whereas the Bonferroni procedure found no significant results.
Although still unfamiliar to many health researchers, the use of false discovery rate control in the context of multiple testing can provide a solid basis for drawing conclusions about statistical significance.
Publisher
Elsevier Inc,Elsevier,Elsevier Limited
Subject
/ Biological and medical sciences
/ Biomedical Research - methods
/ Biomedical Research - standards
/ Data Interpretation, Statistical
/ Deepwater exploration & production
/ FWER
/ Humans
/ P-value
/ Public health. Hygiene-occupational medicine
/ Randomized Controlled Trials as Topic - methods
/ Randomized Controlled Trials as Topic - psychology
/ Studies
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