Document Detail


Exact sample size needed to detect dependence in 2 x 2 x 2 tables.
MedLine Citation:
PMID:  18078486     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
In the Georgia Centenarian Study (Poon et al., Exceptional Longevity, 2006), centenarian cases and young controls are classified according to three categories (age, ethnic origin, and single nucleotide polymorphisms [SNPs] of candidate longevity genes), where each factor has two possible levels. Here we provide methodologies to determine the minimum sample size needed to detect dependence in 2 x 2 x 2 tables based on Fisher's exact test evaluated exactly or by Markov chain Monte Carlo (MCMC), assuming only the case total L and the control total N are known. While our MCMC method uses serial computing, parallel computing techniques are employed to solve the exact sample size problem. These tools will allow researchers to design efficient sampling strategies and to select informative SNPs. We apply our tools to 2 x 2 x 2 tables obtained from a pilot study of the Georgia Centenarians Study, and the sample size results provided important information for the subsequent major study. A comparison between the results of an exact method and those of a MCMC method showed that the MCMC method studied needed much less computation time on average (10.16 times faster on average for situations examined with S.E. = 2.60), but its sample size results were only valid as a rule for larger sample sizes (in the hundreds).
Authors:
Jianliang Dai; Li Li; Sangkyu Kim; Beth Kimball; S Michal Jazwinski; Jonathan Arnold;
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Biometrics     Volume:  63     ISSN:  0006-341X     ISO Abbreviation:  Biometrics     Publication Date:  2007 Dec 
Date Detail:
Created Date:  2007-12-14     Completed Date:  2008-01-22     Revised Date:  2013-06-06    
Medline Journal Info:
Nlm Unique ID:  0370625     Medline TA:  Biometrics     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1245-52     Citation Subset:  IM    
Affiliation:
Genetics Department, University of Georgia, Athens, Georgia 30602, USA.
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MeSH Terms
Descriptor/Qualifier:
Age Distribution
Aging / genetics*
Computer Simulation
Data Interpretation, Statistical*
Georgia / epidemiology
Humans
Longevity / genetics*
Markov Chains
Models, Genetic*
Models, Statistical
Polymorphism, Single Nucleotide / genetics*
Sample Size*
Sex Distribution
Grant Support
ID/Acronym/Agency:
1P01-AG17553/AG/NIA NIH HHS; 5P01 AG017553-03/AG/NIA NIH HHS; P01 AG017553-05/AG/NIA NIH HHS
Comments/Corrections

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