Covariate Analysis of Survival Data: A Small-Sample Study of Cox's Model

Covariate Analysis of Survival Data: A Small-Sample Study of Cox's Model

Cox's proportional-hazards model is frequently used to adjust for covariate effects in survival-data analysis. The small-sample performances of the maximum partial likelihood estimators of the regression parameters in a two-covariate hazard function model are evaluated with respect to bias, var...

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Veröffentlicht in:Biometrics 1982-09, Vol.38 (3), p.685-698
Hauptverfasser: Johnson, Mark E., Tolley, H. Dennis, Bryson, Maurice C., Goldman, Aaron S.
Format: Artikel
Sprache:eng
Schlagworte:
560000 - Biomedical Sciences, Applied Studies
570000 - Health & Safety
Analysis of Variance
Asymptotic value
Biometrics
Censorship
Covariance
Estimation bias
GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
Humans
MATHEMATICAL MODELS
Mathematical monotonicity
MATHEMATICS
Modeling
Models, Biological
MONTE CARLO METHOD
Mortality
Papers on the Analysis of Covariance
PARAMETRIC ANALYSIS
RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTANT EFFECTS ON LIVING ORGS. AND BIOL. MAT
REGRESSION ANALYSIS
Research Design
Sampling bias
Statistical discrepancies
Statistical variance
STATISTICS
SURVIVAL CURVES
SURVIVAL TIME
TIME DEPENDENCE
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Beschreibung
Zusammenfassung:Cox's proportional-hazards model is frequently used to adjust for covariate effects in survival-data analysis. The small-sample performances of the maximum partial likelihood estimators of the regression parameters in a two-covariate hazard function model are evaluated with respect to bias, variance, and power in hypothesis tests. Previous Monte Carlo work on the two-sample problem is reviewed.
ISSN:0006-341X
1541-0420
DOI:10.2307/2530049