A Copula Approach for Detecting Prognostic Genes Associated With Survival Outcome in Microarray Studies

DOI10.1111/J.1541-0420.2007.00802.XzbMath1141.62089OpenAlexW2049910743WikidataQ80278236 ScholiaQ80278236MaRDI QIDQ5449907

Sin-Ho Jung, Pranab Kumar Sen, Kouros Owzar

Publication date: 19 March 2008

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1541-0420.2007.00802.x

zbMATH Keywords

semiparametric modelsurvival analysismultiple testingdependencemultivariate distributionpermutation resampling

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Censored data models (62N01) Medical applications (general) (92C50) Estimation in survival analysis and censored data (62N02)

Uses Software

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Cites Work

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• An introduction to copulas.
• On the simultaneous associativity of F(x,y) and x+y-F(x,y)
• On nonparametric measures of dependence for random variables
• A Concordance Test for Independence in the Presence of Censoring
• A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence
• Inferences on the Association Parameter in Copula Models for Bivariate Survival Data
• Model Selection and Semiparametric Inference for Bivariate Failure-Time Data
• A Direct Approach to False Discovery Rates
• A semiparametric estimation procedure of dependence parameters in multivariate families of distributions
• Estimation of the Association for Bivariate Interval‐censored Failure Time Data
• On a Heuristic Method of Test Construction and its use in Multivariate Analysis

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