Biometrika · 1994 · 5.6K citations · 22 references
Public HealthBiostatisticsClinical EpidemiologyEpidemiologic MethodsSurvival AnalysisHazard FunctionsParametric Survival ModelsSurvival ModelingTime-dependent CovariatesTime-series Analysis In EpidemiologyTime-to-event AnalysisCox RegressionExtended Cox ModelExtended Cox Proportional Hazards ModelNonproportional HazardsTests Of Proportional HazardsTime-varying CoefficientsTime-varying Hazard ModelsWeighted Least Squares
SUMMARY Nonproportional hazards can often be expressed by extending the Cox model to include time varying coefficients; e.g., for a single covariate, the hazard function for subject i is modelled as exp { fl(t)Zi(t)}. A common example is a treatment effect that decreases with time. We show that the function /3(t) can be directly visualized by smoothing an appropriate residual plot. Also, many tests of proportional hazards, including those of Cox (1972), Gill & Schumacher (1987), Harrell (1986), Lin (1991), Moreau, O'Quigley & Mesbah (1985), Nagelkerke, Oosting & Hart (1984), O'Quigley & Pessione (1989), Schoenfeld (1980) and Wei (1984) are related to time-weighted score tests of the proportional hazards hypothesis, and can be visualized as a weighted least-squares line fitted to the residual plot.
22
The Statistical Analysis of Failure Time Data.
Murray Aitkin, John D. Kalbfleisch, Ross L. Prentice · Biometrics · 1981 · 10K citations
Richard A. Brown, Trevor Hastie, Robert Tibshirani · Biometrics · 1991 · 8.3K citations
Partial residuals for the proportional hazards regression model
David Schoenfeld · Biometrika · 1982 · 2.9K citations
Statistical Models Based on Counting Processes
Xavier Bry, Per Kragh Andersen, Ørnulf Borgan et al. · Population · 1997 · 2.9K citations