Modeling Between-Study Heterogeneity for Improved Replicability in Gene Signature Selection and Clinical Prediction-Reference-Cited by-同舟云学术

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Modeling Between-Study Heterogeneity for Improved Replicability in Gene Signature Selection and Clinical Prediction

Published:2019-10-29 Issue:531 Volume:115 Page:1125-1138
ISSN:0162-1459
Container-title:Journal of the American Statistical Association
language:en
Short-container-title:Journal of the American Statistical Association

Author:

Rashid Naim U.¹²,Li Quefeng¹,Yeh Jen Jen²³⁴,Ibrahim Joseph G.¹

Affiliation:

1. Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC;

2. Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC;

3. Department of Surgery, University of North Carolina at Chapel Hill, Chapel Hill, NC;

4. Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/01621459.2019.1671197

Reference35 articles.

1. Rank discriminants for predicting phenotypes from RNA expression

2. switchBox: an R package for k–Top Scoring Pairs classifier development

3. Joint Variable Selection for Fixed and Random Effects in Linear Mixed-Effects Models

4. Coordinate descent algorithms for nonconvex penalized regression, with applications to biological feature selection

5. Group descent algorithms for nonconvex penalized linear and logistic regression models with grouped predictors

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