Add to ORKGDescription Flexible parametric models for time-to-event data, including the Royston-Parmar spline model, generalized gamma and generalized F distributions. Any user-defined parametric distribution can be fitted, given at least an R function defining the probabil-ity density or hazard. There are also tools for fitting and predicting from fully parametric multi-state models
Depends R (> = 2.2.1), gamlss, survival Description This is an add on package to GAMLSS. It allow...
It is usual in time-to-event data to have more than one event of interest, for example, time to deat...
In cancer research, study of the hazard function provides useful information on the disease dynamic,...
Multistate models are increasingly being used to model complex disease profiles. By modelling transi...
Background: Parametric modelling of survival data is important and reimbursement decisions may depen...
<p><sup>‡</sup> Not pursued by the authors</p><p><i>Abbreviations</i>: ARR (Absolute Risk Reduction)...
Background: Parametric modelling of survival data is important and reimbursement decisions may depen...
In cancer research, study of the hazard function provides useful insights into disease dynamics, as ...
This vignette of examples supplements the main flexsurv user guide. Keywords:˜survival. 1. Examples ...
Description Simultaneous tests and confidence intervals for general linear hypotheses in parametric ...
Multilevel mixed effects survival models are used in the analysis of clustered survival data, such a...
Since its introduction to a wondering public in 1972, the Cox proportional hazards regression model ...
Non-PH parametric survival modelling is developed within the framework of the mul tiple logistic fun...
Description This package fits multiple variable mixtures of various parametric proportional haz-ard ...
Suggests lme4, nnet, xtable Description This package implements cumulative link (mixed) models also ...
Depends R (> = 2.2.1), gamlss, survival Description This is an add on package to GAMLSS. It allow...
It is usual in time-to-event data to have more than one event of interest, for example, time to deat...
In cancer research, study of the hazard function provides useful information on the disease dynamic,...
Multistate models are increasingly being used to model complex disease profiles. By modelling transi...
Background: Parametric modelling of survival data is important and reimbursement decisions may depen...
<p><sup>‡</sup> Not pursued by the authors</p><p><i>Abbreviations</i>: ARR (Absolute Risk Reduction)...
Background: Parametric modelling of survival data is important and reimbursement decisions may depen...
In cancer research, study of the hazard function provides useful insights into disease dynamics, as ...
This vignette of examples supplements the main flexsurv user guide. Keywords:˜survival. 1. Examples ...
Description Simultaneous tests and confidence intervals for general linear hypotheses in parametric ...
Multilevel mixed effects survival models are used in the analysis of clustered survival data, such a...
Since its introduction to a wondering public in 1972, the Cox proportional hazards regression model ...
Non-PH parametric survival modelling is developed within the framework of the mul tiple logistic fun...
Description This package fits multiple variable mixtures of various parametric proportional haz-ard ...
Suggests lme4, nnet, xtable Description This package implements cumulative link (mixed) models also ...
Depends R (> = 2.2.1), gamlss, survival Description This is an add on package to GAMLSS. It allow...
It is usual in time-to-event data to have more than one event of interest, for example, time to deat...
In cancer research, study of the hazard function provides useful information on the disease dynamic,...