Cox regression model has an important and glaring place in survival analysis. The key assumption is proportional hazards and violation of this assumption can invalidate outcomes of a study. Our approach will be to use Cox regression model with weighted estimation for a survival data set that includes both proportional and nonproportional hazards. We carried out a simulation study, considering different censoring rates, sample sizes, and tied observations. Simulation results are interpreted and discussed with the results obtained by traditional Cox regression model. Cox regression model with N-Prentice weighting function serves as a better model under all simulation scenario
This paper discusses techniques to generate survival times for simulation studies regarding Cox prop...
The advancement in data acquiring technology continues to see survival data sets with many covariate...
One of the most popular models for survival analysis is the Cox proportional hazard model. In this m...
Cox regression model has an important and glaring place in survival analysis. The key assumption is ...
Cox regression is a well-known approach for modeling censored survival data. However, the model has ...
This thesis consists of four papers about the assumption of proportional hazards for the Cox model i...
The Cox regression, a semi-parametric method of survival analysis, is extremely popular in biomedica...
Cox's regression model for the analysis of survival data relies on the proportional hazards assumpti...
An investigation was performed to evaluate the properties of three estimators for the regression par...
The Cox model is one of the most widely used semi-parametric models in survival data analysis. For v...
The primary objective of this thesis is to explore the effect of omitting a strong prognostic factor...
Survival analysis examines and models the time it takes for events to occur, termed survival time. T...
We extend the Cox proportional hazards model to cases when the exposure is a densely sampled functio...
The Cox regression model is a cornerstone of modern survival analysis and is widely used in many oth...
Proportional Hazard regression model for censored survival data often specifies that covariates have...
This paper discusses techniques to generate survival times for simulation studies regarding Cox prop...
The advancement in data acquiring technology continues to see survival data sets with many covariate...
One of the most popular models for survival analysis is the Cox proportional hazard model. In this m...
Cox regression model has an important and glaring place in survival analysis. The key assumption is ...
Cox regression is a well-known approach for modeling censored survival data. However, the model has ...
This thesis consists of four papers about the assumption of proportional hazards for the Cox model i...
The Cox regression, a semi-parametric method of survival analysis, is extremely popular in biomedica...
Cox's regression model for the analysis of survival data relies on the proportional hazards assumpti...
An investigation was performed to evaluate the properties of three estimators for the regression par...
The Cox model is one of the most widely used semi-parametric models in survival data analysis. For v...
The primary objective of this thesis is to explore the effect of omitting a strong prognostic factor...
Survival analysis examines and models the time it takes for events to occur, termed survival time. T...
We extend the Cox proportional hazards model to cases when the exposure is a densely sampled functio...
The Cox regression model is a cornerstone of modern survival analysis and is widely used in many oth...
Proportional Hazard regression model for censored survival data often specifies that covariates have...
This paper discusses techniques to generate survival times for simulation studies regarding Cox prop...
The advancement in data acquiring technology continues to see survival data sets with many covariate...
One of the most popular models for survival analysis is the Cox proportional hazard model. In this m...