Variable selection – A review and recommendations for the practicing statistician

DOI10.1002/bimj.201700067zbMath1429.62532OpenAlexW2782176193WikidataQ47225500 ScholiaQ47225500MaRDI QIDQ4563248

Christine Wallisch, Daniela Dunkler, Georg Heinze

Publication date: 31 May 2018

Published in: Biometrical Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/bimj.201700067

zbMATH Keywords

resamplingstatistical modelconfidence interval estimationcensored survival datapenalized likelihoodstepwise selectionchange-in-estimate criterion

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (14)

Bayes factor asymptotics for variable selection in the Gaussian process framework ⋮ Variable Selection With Second-Generation P-Values ⋮ Asymptotics of AIC, BIC and \(C_p\) model selection rules in high-dimensional regression ⋮ Extended Bayesian endemic–epidemic models to incorporate mobility data into COVID‐19 forecasting ⋮ Regression models for order‐of‐addition experiments ⋮ Doug Altman: Driving critical appraisal and improvements in the quality of methodological and medical research ⋮ Is there a role for statistics in artificial intelligence? ⋮ Using reference models in variable selection ⋮ Variable selection by searching for good subsets ⋮ An automated exact solution framework towards solving the logistic regression best subset selection problem ⋮ Model choice for regression models with a categorical response ⋮ Variable selection in double/debiased machine learning for causal inference: an outcome-adaptive approach ⋮ Fast and approximate exhaustive variable selection for generalised linear models with APES ⋮ Visual research on the trustability of classical variable selection methods in Cox regression

Uses Software

• rms
• SAS
• glmnet
• aplore3
• ElemStatLearn
• SAS/STAT
• shrink
• abe

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