We derive the proper form of the Akaike information criterion for variable selection for mixture cure models, which are often fit via the expectation-maximization algorithm. Separate covariate sets may be used in the mixture components. The selection criteria are applicable to survival models for right-censored data with multiple competing risks and allow for the presence of an insusceptible group. The method is illustrated on credit loan data, with pre-payment and default as events and maturity as the insusceptible case and is used in a simulation study.publisher: Elsevier articletitle: An Akaike information criterion for multiple event mixture cure models journaltitle: European Journal of Operational Research articlelink: http://dx.doi.or...
In survival analysis, the survival time is assumed to follow a non-negative distribution, such as th...
In survival analysis, it often happens that a certain fraction of the subjects under study never exp...
This paper introduces a general framework of survival mixture models (SMMs) that addresses the unobs...
We derive the proper form of the Akaike information criterion for variable selection for mixture cur...
We examine the problem of jointly selecting the number of components and variables in finite mixture...
Due to more strict regulations as a result of the Basel accords, survival analysis is becoming more ...
We examine the problem of jointly selecting the number of components and variables in finite mixture...
Extending standard survival analysis techniques, multiple event mixture cure models are used in orde...
In survival analysis, it is generally assumed that every individual will someday ex- perience the ev...
Despite the development and adoption of time-to-event/survival analysis techniques in the research f...
Analysis of the survival data with a subgroup of cured subjects arising in a clinical trial is commo...
The prediction of the time of default in a credit risk setting via survival analysis needs to take a...
This paper focuses on the Akaike information criterion, AIC, for linear mixed-effects models in the ...
In survival analysis it often happens that a certain fraction of the subjects under study never expe...
International audienceCure models have been developed to analyze failure time data with a cured frac...
In survival analysis, the survival time is assumed to follow a non-negative distribution, such as th...
In survival analysis, it often happens that a certain fraction of the subjects under study never exp...
This paper introduces a general framework of survival mixture models (SMMs) that addresses the unobs...
We derive the proper form of the Akaike information criterion for variable selection for mixture cur...
We examine the problem of jointly selecting the number of components and variables in finite mixture...
Due to more strict regulations as a result of the Basel accords, survival analysis is becoming more ...
We examine the problem of jointly selecting the number of components and variables in finite mixture...
Extending standard survival analysis techniques, multiple event mixture cure models are used in orde...
In survival analysis, it is generally assumed that every individual will someday ex- perience the ev...
Despite the development and adoption of time-to-event/survival analysis techniques in the research f...
Analysis of the survival data with a subgroup of cured subjects arising in a clinical trial is commo...
The prediction of the time of default in a credit risk setting via survival analysis needs to take a...
This paper focuses on the Akaike information criterion, AIC, for linear mixed-effects models in the ...
In survival analysis it often happens that a certain fraction of the subjects under study never expe...
International audienceCure models have been developed to analyze failure time data with a cured frac...
In survival analysis, the survival time is assumed to follow a non-negative distribution, such as th...
In survival analysis, it often happens that a certain fraction of the subjects under study never exp...
This paper introduces a general framework of survival mixture models (SMMs) that addresses the unobs...