Rationale and applications of survival tree and survival ensemble methods

DOI10.1007/s11336-014-9413-1zbMath1323.62127OpenAlexW2044076969WikidataQ35537310 ScholiaQ35537310MaRDI QIDQ888036

John J. McArdle, Yan Zhou

Publication date: 4 November 2015

Published in: Psychometrika (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc4409541

zbMATH Keywords

survival analysisrecursive partitioningrandom forestsstatistical learningsurvival trees

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Learning and adaptive systems in artificial intelligence (68T05) Applications of statistics to psychology (62P15)

Related Items (3)

Mixture survival trees for cancer risk classification ⋮ Interval Censored Recursive Forests ⋮ Optimal survival trees

Uses Software

• rpart
• party
• ipred
• randomSurvivalForest
• partykit
• randomForest

Cites Work

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• Bagging predictors
• Random survival forests
• Statistical learning from a regression perspective
• Consistency of random survival forests
• Stratification by stepwise regression, correspondence analysis and recursive partition: A comparison of three methods of analysis for survival data with covariates
• Recursive partitioning in the health sciences
• Tree-based multivariate regression and density estimation with right-censored data
• Martingale-based residuals for survival models
• Survival ensembles
• Regression Trees for Censored Data
• Survival Trees by Goodness of Split
• Problems in the Analysis of Survey Data, and a Proposal
• Random forests

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