An evaluation of penalised survival methods for developing prognostic models with rare events

Statistics in Medicine

Volumn 31, Issue 11-12, 2012, Pages 1150-1161

  Ambler, G ^a   Seaman, S ^b   Omar, R Z ^a  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

^b MRC BIOSTATISTICS UNIT   (United Kingdom)

Author keywords

Garotte; Lasso; Penalised regression; Prognostic models; Ridge; Risk prediction; Shrinkage; Survival analysis; Variable selection

Indexed keywords

ACCURACY; ANALYTIC METHOD; ARTICLE; DATA BASE; INTERMETHOD COMPARISON; MATHEMATICAL COMPUTING; MAXIMUM LIKELIHOOD METHOD; PENALISED SURVIVAL METHOD; PREDICTION; PROGNOSIS; PROPORTIONAL HAZARDS MODEL; SIMULATION; STATISTICAL PARAMETERS; STATISTICAL SIGNIFICANCE; SURVIVAL;

CARCINOMA, SQUAMOUS CELL; COMPUTER SIMULATION; FEMALE; HEART VALVE PROSTHESIS; HUMANS; INCIDENCE; LIKELIHOOD FUNCTIONS; LONDON; MALE; PENILE NEOPLASMS; PROGNOSIS; PROSTHESIS FAILURE; SURVIVAL ANALYSIS;

EID: 84861193203     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.4371     Document Type: Article

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