In survival analysis or medical studies each person can be exposed to more than one type of outcomes which occurrence of one of them prevents the other outcomes' occurrence; this situation is called the competing risks. Assessing the effect of covariates on the survival time (or failure time) is one of the purposes in competing risks analysis. In this paper, we study a competing risks model in the presence of covariates when the causes of failures follow generalized Weibull distributions. Covariates are entered to the model through the scale parameter of this distribution. Also in this study the competing risks are considered to be independent. Parameter estimation has been done by the maximum likelihood approach, in a real data set and a s...
Time-dependent covariates are frequently encountered in regression analysis for event history data a...
In this article, a competing risk model is analyzed in the presence of complete and censored data wh...
Generally, survival analysis is a significant aspect of statistics that helps in anticipating possib...
In survival analysis, individuals may fail due to multiple causes of failure called competing risks ...
The thesis concerns regression models related to the competing risks setting in survival analysis an...
In several studies in Survival Analysis, the cause of failure / death of items or individuals may be...
Prognostic studies often involve modeling competing risks, where an individual can experience only o...
Competing risks data usually arises in studies in which the failure of an individual may be classifi...
Competing risks are frequently overlooked, and the event of interest is analyzed with conventional s...
New statistical models for analysing survival data in an intensive care unit context have recently b...
The possible occurrence of multiple events during follow-up is a common situation in several clinica...
Competing risks analysis with two causes of failure was considered. Since inde-pendence of causes ar...
The aim with this Master's thesis has been to develop a method of fitting a Phase-type model to...
The study deals with the methods of statistical analysis in the situation of competing risks in the ...
In the competing risks model, a unit is exposed to several risks at the same time, but it is assumed...
Time-dependent covariates are frequently encountered in regression analysis for event history data a...
In this article, a competing risk model is analyzed in the presence of complete and censored data wh...
Generally, survival analysis is a significant aspect of statistics that helps in anticipating possib...
In survival analysis, individuals may fail due to multiple causes of failure called competing risks ...
The thesis concerns regression models related to the competing risks setting in survival analysis an...
In several studies in Survival Analysis, the cause of failure / death of items or individuals may be...
Prognostic studies often involve modeling competing risks, where an individual can experience only o...
Competing risks data usually arises in studies in which the failure of an individual may be classifi...
Competing risks are frequently overlooked, and the event of interest is analyzed with conventional s...
New statistical models for analysing survival data in an intensive care unit context have recently b...
The possible occurrence of multiple events during follow-up is a common situation in several clinica...
Competing risks analysis with two causes of failure was considered. Since inde-pendence of causes ar...
The aim with this Master's thesis has been to develop a method of fitting a Phase-type model to...
The study deals with the methods of statistical analysis in the situation of competing risks in the ...
In the competing risks model, a unit is exposed to several risks at the same time, but it is assumed...
Time-dependent covariates are frequently encountered in regression analysis for event history data a...
In this article, a competing risk model is analyzed in the presence of complete and censored data wh...
Generally, survival analysis is a significant aspect of statistics that helps in anticipating possib...