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Selection of Influential Genetic Markers Among a Large Number of Candidates Based on Effect Estimation Rather than Hypothesis Testing: An Approach for Genome-Wide Association Studies.

Strömberg, Ulf LU ; Björk, Jonas LU ; Broberg Palmgren, Karin LU ; Mertens, Fredrik LU and Vineis, Paolo (2008) In Epidemiology 19. p.302-308
Abstract
In epidemiologic studies on direct genetic associations, hypothesis testing is primarily considered for evaluating the effects of each candidate genetic marker, eg, single nucleotide polymorphisms. To help investigators protect themselves from over-interpreting statistically significant findings that are not likely to signify a true effect-a problem connected to multiple comparisons-consideration of the false-positive report probability has been proposed. There have also been arguments advocating estimation of effect size rather than hypothesis testing (P value). Here, we propose an estimation-based approach that offers an attractive alternative to the test-based false-positive report probability, when the task is to select promising... (More)
In epidemiologic studies on direct genetic associations, hypothesis testing is primarily considered for evaluating the effects of each candidate genetic marker, eg, single nucleotide polymorphisms. To help investigators protect themselves from over-interpreting statistically significant findings that are not likely to signify a true effect-a problem connected to multiple comparisons-consideration of the false-positive report probability has been proposed. There have also been arguments advocating estimation of effect size rather than hypothesis testing (P value). Here, we propose an estimation-based approach that offers an attractive alternative to the test-based false-positive report probability, when the task is to select promising genetic markers for further analyses. We discuss the potential of this estimation-based approach for genome-wide association studies. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Epidemiology
volume
19
pages
302 - 308
publisher
Wolters Kluwer Health/LWW
external identifiers
  • pmid:18300718
  • wos:000253401400024
  • scopus:39149138414
ISSN
1531-5487
DOI
10.1097/EDE.0b013e3181632c3d
language
English
LU publication?
yes
id
f1c553ac-f76d-4578-9607-f57b51553a0d (old id 1041502)
alternative location
http://www.ncbi.nlm.nih.gov/pubmed/18300718?dopt=Abstract
date added to LUP
2008-03-06 15:47:01
date last changed
2017-01-01 07:38:35
@article{f1c553ac-f76d-4578-9607-f57b51553a0d,
  abstract     = {In epidemiologic studies on direct genetic associations, hypothesis testing is primarily considered for evaluating the effects of each candidate genetic marker, eg, single nucleotide polymorphisms. To help investigators protect themselves from over-interpreting statistically significant findings that are not likely to signify a true effect-a problem connected to multiple comparisons-consideration of the false-positive report probability has been proposed. There have also been arguments advocating estimation of effect size rather than hypothesis testing (P value). Here, we propose an estimation-based approach that offers an attractive alternative to the test-based false-positive report probability, when the task is to select promising genetic markers for further analyses. We discuss the potential of this estimation-based approach for genome-wide association studies.},
  author       = {Strömberg, Ulf and Björk, Jonas and Broberg Palmgren, Karin and Mertens, Fredrik and Vineis, Paolo},
  issn         = {1531-5487},
  language     = {eng},
  pages        = {302--308},
  publisher    = {Wolters Kluwer Health/LWW},
  series       = {Epidemiology},
  title        = {Selection of Influential Genetic Markers Among a Large Number of Candidates Based on Effect Estimation Rather than Hypothesis Testing: An Approach for Genome-Wide Association Studies.},
  url          = {http://dx.doi.org/10.1097/EDE.0b013e3181632c3d},
  volume       = {19},
  year         = {2008},
}