Abstract
Plasmode is a term coined several years ago to describe data sets that are derived from real data but for which some truth is known. Omic techniques, most especially microarray and genome wide association studies, have catalyzed a new zeitgeist of data sharing that is making data and data sets publicly available on an unprecedented scale. Coupling such data resources with a science of plasmode use would allow statistical methodologists to vet proposed techniques empirically (as opposed to only theoretically) and with data that are by definition realistic and representative. We illustrate the technique of empirical statistics by consideration of a common task when analyzing high dimensional data: The simultaneous testing of hundreds or thousands of hypotheses to determine which, if any, show statistical significance warranting follow-on research. the now-common practice of multiple testing in high dimensional experiment (HDE) settings has generated new methods for detecting statistically significant results. Although such methods have heretofore been subject to comparative performance analysis using simulated data, simulating data that realistically reflect data from an actual HDE remains a challenge. We describe a simulation procedure using actual data from an HDE where some truth regarding parameters of interest is known. We use the procedure to compare estimates for the proportion of true null hypotheses, the false discovery rate (FDR), and a local version of FDR obtained from 15 different statistical methods. © 2008 Gadbury et al.
Recommended Citation
G. L. Gadbury et al., "Evaluating Statistical Methods using Plasmode Data Sets in the Age of Massive Public Databases: An Illustration using False Discovery Rates," PLoS Genetics, vol. 4, no. 6, article no. e1000098, Public Library of Science, Jun 2008.
The definitive version is available at https://doi.org/10.1371/journal.pgen.1000098
Department(s)
Mathematics and Statistics
Publication Status
Open Access
International Standard Serial Number (ISSN)
1553-7404; 1553-7390
Document Type
Article - Journal
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2024 The Authors, All rights reserved.
Creative Commons Licensing
This work is licensed under a Creative Commons Attribution 4.0 License.
Publication Date
01 Jun 2008
PubMed ID
18566659
Comments
National Institute of Diabetes and Digestive and Kidney Diseases, Grant P30DK056336