Journal of Modern Applied Statistical Methods · 2015 · 11 citations · 22 references
Public HealthBiostatisticsInfertilityReproductive HealthSurvival AnalysisHazard FunctionsParametric Survival ModelsProportional Hazards AssumptionsSurvival ModelingTime-dependent CovariatesTime-to-event AnalysisAssumption CheckingCox RegressionHazard Rate AnalysisHazard Rate EstimationNon-proportional Hazards ModelingProportional Hazards ViolationProportionalitySemi-parametric Regression
The application of survival analysis has extended the importance of statistical methods for time to event data that incorporate time dependent covariates. The Cox proportional hazards model is one such method that is widely used. An extension of the Cox model with time-dependent covariates was adopted when proportionality assumption are violated. The purpose of this study is to validate the model assumption when hazard rate varies with time. This approach is applied to model data on duration of infertility subject to time varying covariate. Validity is assessed by a set of simulation experiments and results indicate that a non proportional hazard model performs well in the phase of violated assumptions of the Cox proportional hazards.
22
Choice Reviews Online · 1990 · 35.7K citations
Survival Analysis: A Self-Learning Text
Mark Carpenter · Technometrics · 1997 · 1.4K citations