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Volumn 72, Issue 3, 2016, Pages 897-906
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Addressing issues associated with evaluating prediction models for survival endpoints based on the concordance statistic
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Author keywords
Coarsening at random; Concordance statistic; Inverse probability of censoring weighting; Noncoarsening at random; Predictive accuracy; Sensitivity analysis; Survival endpoint
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Indexed keywords
CLUSTERING ALGORITHMS;
DIAGNOSIS;
DISEASES;
FORECASTING;
INVERSE PROBLEMS;
UROLOGY;
BIOMEDICAL RESEARCH;
COARSENING AT RANDOM;
COARSENINGS;
CONCORDANCE STATISTIC;
DISEASE RISKS;
INVERSE PROBABILITY OF CENSORING WEIGHTING;
NONCOARSENING AT RANDOM;
PREDICTION MODELLING;
PREDICTIVE ACCURACY;
SURVIVAL ENDPOINT;
SENSITIVITY ANALYSIS;
ACCURACY ASSESSMENT;
CANCER;
INVERSE ANALYSIS;
NUMERICAL MODEL;
PERFORMANCE ASSESSMENT;
PREDICTION;
PROBABILITY;
SENSITIVITY ANALYSIS;
SURVIVAL;
COMPUTER SIMULATION;
HUMAN;
MALE;
MORTALITY;
PREDICTIVE VALUE;
PROBABILITY;
PROGNOSIS;
PROSTATECTOMY;
PROSTATIC NEOPLASMS;
RECURRENT DISEASE;
RISK;
STATISTICAL MODEL;
SURVIVAL ANALYSIS;
COMPUTER SIMULATION;
HUMANS;
MALE;
MODELS, STATISTICAL;
PREDICTIVE VALUE OF TESTS;
PROBABILITY;
PROGNOSIS;
PROSTATECTOMY;
PROSTATIC NEOPLASMS;
RECURRENCE;
RISK;
SURVIVAL ANALYSIS;
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EID: 85027931133
PISSN: None
EISSN: 15410420
Source Type: Journal
DOI: 10.1111/biom.12470 Document Type: Article |
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Times cited : (9)
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References (30)
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