Continuous‐time multistate survival models can be used to describe health‐related processes over time. In the presence of interval‐censored times for transitions between the living states, the likelihood is constructed using transition probabilities. Models can be specified using parametric or semiparametric shapes for the hazards. Semiparametric hazards can be fitted using P‐splines and penalised maximum likelihood estimation. This paper presents a method to estimate flexible multistate models that allow for parametric and semiparametric hazard specifications. The estimation is based on a scoring algorithm. The method is illustrated with data from the English Longitudinal Study of Ageing
Multi-state models can be successfully used for describing complicated event history data, for examp...
We consider the mixed dicrete-continuous pattern of observation in a multi-state model; this is a cl...
Interval-censored multi-state data arise in many studies of chronic diseases, where the health statu...
Continuous-time multi-state Markov models can be used to describe transitions over time across healt...
Continuous-time multi-state models are widely used in modeling longitudinal data of disease processe...
Multistate models are increasingly being used to model complex disease profiles. By modelling transi...
This paper presents a parametric method of fitting semi-Markov models with piecewise-constant hazard...
Multi-state models provide a unified framework for the description of the evolution of discrete phen...
Multi-state models provide a unified framework for the description of the evolution of discrete phen...
Background and objective: There is increasing interest in multi-state modelling of health-related s...
In this paper, our aim is to measure mortality rates which are specific to individual observable fac...
peer-reviewedWe develop flexible multiparameter regression (MPR) survival models for interval‐censor...
Although semi- and non-parametric approaches are frequently used to analyse survival data, there are...
Multi-state models can be successfully used for describing complicated event history data, for examp...
We consider the mixed dicrete-continuous pattern of observation in a multi-state model; this is a cl...
Interval-censored multi-state data arise in many studies of chronic diseases, where the health statu...
Continuous-time multi-state Markov models can be used to describe transitions over time across healt...
Continuous-time multi-state models are widely used in modeling longitudinal data of disease processe...
Multistate models are increasingly being used to model complex disease profiles. By modelling transi...
This paper presents a parametric method of fitting semi-Markov models with piecewise-constant hazard...
Multi-state models provide a unified framework for the description of the evolution of discrete phen...
Multi-state models provide a unified framework for the description of the evolution of discrete phen...
Background and objective: There is increasing interest in multi-state modelling of health-related s...
In this paper, our aim is to measure mortality rates which are specific to individual observable fac...
peer-reviewedWe develop flexible multiparameter regression (MPR) survival models for interval‐censor...
Although semi- and non-parametric approaches are frequently used to analyse survival data, there are...
Multi-state models can be successfully used for describing complicated event history data, for examp...
We consider the mixed dicrete-continuous pattern of observation in a multi-state model; this is a cl...
Interval-censored multi-state data arise in many studies of chronic diseases, where the health statu...