Deriving and comparing the distribution for the number of false positives in single step methods to control k-FWER

Jeffrey C. Miecznikowski; David Gold; Lori Shepherd; Song Liu

doi:10.1016/j.spl.2011.06.011

Deriving and comparing the distribution for the number of false positives in single step methods to control k-FWER

Jeffrey C. Miecznikowski
, David Gold
, Lori Shepherd
, Song Liu

Department of Biostatistics

SUNY Buffalo
Roswell Park Cancer Institute

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

In a multiple testing setting, the investigator is faced with choosing a method for controlling the Type I error rate. In this manuscript, we derive and compare the exact distribution for the number of false positives under a commonly used distribution. The results from this work can be extended to derive the distribution of other error control quantities, while the conclusions from our simulations can be used to power future studies.

Original language	English
Pages (from-to)	1695-1705
Number of pages	11
Journal	Statistics and Probability Letters
Volume	81
Issue number	11
DOIs	https://doi.org/10.1016/j.spl.2011.06.011
State	Published - Nov 2011

Keywords

False positives
Family wise error rate
Hypothesis testing
Multiple testing

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10.1016/j.spl.2011.06.011

Cite this

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abstract = "In a multiple testing setting, the investigator is faced with choosing a method for controlling the Type I error rate. In this manuscript, we derive and compare the exact distribution for the number of false positives under a commonly used distribution. The results from this work can be extended to derive the distribution of other error control quantities, while the conclusions from our simulations can be used to power future studies.",

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AU - Miecznikowski, Jeffrey C.

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AU - Shepherd, Lori

AU - Liu, Song

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AB - In a multiple testing setting, the investigator is faced with choosing a method for controlling the Type I error rate. In this manuscript, we derive and compare the exact distribution for the number of false positives under a commonly used distribution. The results from this work can be extended to derive the distribution of other error control quantities, while the conclusions from our simulations can be used to power future studies.

KW - False positives

KW - Family wise error rate

KW - Hypothesis testing

KW - Multiple testing

UR - https://www.scopus.com/pages/publications/79960655749

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M3 - Article

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JO - Statistics and Probability Letters

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ER -

Deriving and comparing the distribution for the number of false positives in single step methods to control k-FWER

Abstract

Keywords

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