State of the art in selection of variables and functional forms in multivariable analysis—outstanding issues

被引：158
作者：
Willi Sauerbrei
Aris Perperoglou
Matthias Schmid
Michal Abrahamowicz
Heiko Becher
Harald Binder
Daniela Dunkler
Frank E. Harrell
Patrick Royston
Georg Heinze
机构：
[1] University of Freiburg,Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center
[2] Data Science and Artificial Intelligence AstraZeneca,Department of Medical Biometry, Informatics and Epidemiology, Faculty of Medicine
[3] University of Bonn,McGill University Health Centre
[4] McGill University,Institute for Medical Biometry and Epidemiology
[5] University Medical Center Hamburg-Eppendorf,Section for Clinical Biometrics, Center for Medical Statistics, Informatics and Intelligent Systems
[6] Medical University of Vienna,Department of Biostatistics, School of Medicine
[7] Vanderbilt University,MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology
[8] University College London,undefined
来源：
Diagnostic and Prognostic Research | / 4卷 / 1期
关键词：
Descriptive modelling; Methods for variable selection; Spline procedures; Fractional polynomials; Categorisation; Bias; Shrinkage; Empirical evidence; STRATOS initiative;
D O I：
10.1186/s41512-020-00074-3
中图分类号：
学科分类号：
摘要：
引用
收藏
相关论文
共 339 条
[1]  
Abrahamowicz M(1997)Flexible modelling of the effects of serum cholesterol on coronary heart disease mortality Am J Epidemiol 145 714-729
[2]  
du Berger R(1989)Bootstrap investigation of the stability of a Cox regression model Stat Med 8 771-783
[3]  
Grover SA(1994)The dangers of using ‘optimal’cutpoints in the evaluation of prognostic factors J Nat Cancer Inst 86 829-835
[4]  
Altman DG(2012)Reporting recommendations for tumor marker prognostic studies (REMARK): explanation and elaboration PLoS Med 9 425-438
[5]  
Andersen PK(2012)Variable selection in additive models using P-splines Technometrics 54 959-967
[6]  
Altman DG(2015)Leisure Time physical activity and mortality. A detailed pooled analysis of the dose-response relationship JAMA Intern Med 175 95-118
[7]  
Lausen B(2015)The practical utility of incorporating model selection uncertainty into prognostic models for survival data Stat Model 5 686-700
[8]  
Sauerbrei W(2012)Analysing covariates with spike at zero. a modified FP procedure and conceptual issues Biometrical J 54 3781-3801
[9]  
Schumacher M(2004)Using generalized additive models to reduce residual confounding Stat Med 23 14-2277
[10]  
Altman DG(2008)Allowing for mandatory covariates in boosting estimation of sparse high-dimensional survival models BMC Bioinform 9 2262-218
12345678910