Training course at Lifetime Data Science conference 2023

I’m slightly (very) late in advertising this, but I will be at the 3rd Conference on Lifetime Data Science, to be held in Raleigh, North Carolina, USA, during May 31 – June 2, 2023, teaching a one-day course on Flexible parametric competing risks and multi-state models. Full conference details are here. The programme looks ratherContinue reading “Training course at Lifetime Data Science conference 2023”

Introducing the {msm.stacked} R package

Today we introduce {msm.stacked}, an R package that can be used to simplify the calculation of state transition probabilities over time and the creation of stacked probability plots from multi-state model fits from the {msm} package. Let me show you some examples of the package functionality in practice. We start by building upon the exampleContinue reading “Introducing the {msm.stacked} R package”

Defining a transition matrix for multi-state modelling

In this post we’ll take a look at how to define a custom transition matrix for use with our multistate package in Stata. The transition matrix A transition matrix governs the movement of a process between possible states. Within multi-state survival analysis, and particularly, the implementation of multi-state models in Stata, the transition matrix containsContinue reading “Defining a transition matrix for multi-state modelling”

multistate v4.4.0: semi-parametric multi-state modelling

multistate version 4.4.0 has been released! Ok, that may have happened a few weeks ago… The headlines: predictms now supports the Cox model as a transition model, estimated usingmerlin or stmerlin Predictions from a multi-state Cox model are implemented using asimulation approach Supported predictions from a multi-state Cox model include transitionprobabilities, probability, and length ofContinue reading “multistate v4.4.0: semi-parametric multi-state modelling”