A Monte Carlo approach for change-point detection in the Cox proportional hazards model

Statistics in Medicine

Volumn 27, Issue 19, 2008, Pages 3894-3909

  Liu, Mengling ^a   Lu, Wenbin ^b   Shao, Yongzhao ^a,c  

^a NEW YORK UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b NORTH CAROLINA STATE UNIVERSITY   (United States)

^c Iowa State University   (United States)

Author keywords

Martingale; Multiple change points; Partial likelihood; Resampling; Score test

Indexed keywords

CARMUSTINE; PLACEBO;

ARTICLE; CANCER SURVIVAL; CLINICAL TRIAL; DATA ANALYSIS; DRUG EFFICACY; DRUG SAFETY; GLIOBLASTOMA; HUMAN; KAPLAN MEIER METHOD; MATHEMATICAL ANALYSIS; MAXIMUM LIKELIHOOD METHOD; MONTE CARLO METHOD; NEUROSURGERY; PROPORTIONAL HAZARDS MODEL; SCORING SYSTEM; SIMULATION; STATISTICAL ANALYSIS; STATISTICAL MODEL; STATISTICAL SIGNIFICANCE; SURVIVAL; THEORY; TIME; TREATMENT OUTCOME;

COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; ENDPOINT DETERMINATION; GLIOMA; HUMANS; LIKELIHOOD FUNCTIONS; MONTE CARLO METHOD; PROPORTIONAL HAZARDS MODELS; RANDOMIZED CONTROLLED TRIALS AS TOPIC; SAMPLE SIZE; STATISTICAL DISTRIBUTIONS; TREATMENT OUTCOME;

EID: 50449086073     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.3214     Document Type: Article

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