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Flexible parametric survival analysis with frailty, take two
Hi everyone, Today we are going to continue learning about flexible parametric survival models with random effects, as a follow-up to a previous post on our blog. Specifically, we are going to replicate the analysis from that post, but with a twist:…
Biostatistics & Epidemiology Summer School returns!
I’m delighted to say that the Summer School on Modern Methods in Biostatistics and Epidemiology is returning to the picturesque CastelBrando with a huge range of courses in June 2023! Join me in Treviso, Italy, where I will be back…
stmt: Modelling multiple timescales using flexible parametric survival models in Stata
After many years of working on the stmt package in Stata, our paper Flexible parametric survival analysis with multiple timescales: Estimation and implementation using stmt was recently published in the Stata Journal (1). stmt can be installed by typing in…
Hello from Hannah!
Although I’m not completely new at Red Door Analytics, it’s probably about time that I said a quick hello to introduce myself. So hello! I joined Red Door back in August 2022 as the Director of Applied Biostatistics, and have…
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…
Welcome, Alessandro!
Hi everyone, It’s Alessandro writing – I joined Red Door Analytics as a full-time Senior Biostatistician on the 1st of November, and I am taking this opportunity to introduce myself. Originally from Italy, where I studied for my undergraduate and…
Multivariate joint longitudinal-survival models
Joint longitudinal-survival models have been widely developed, but there are many avenues of research where they are lacking in terms of methodological development, and importantly, accessible implementations. We think merlin fills a few gaps. In this post, we’ll take a…
Simulation and estimation of three-level survival models: IPD meta-analysis of recurrent event data
In this example I’ll look at the analysis of clustered survival data with three levels. This kind of data arises in the meta-analysis of recurrent event times, where we have observations (events or censored), k (level 1), nested within patients,…
Probabilistic sensitivity analysis and survival models
Today we’re going to take a little look into probabilistic sensitivity analysis (PSA), and how it can be implemented within the context of survival analysis. Now PSA is used extensively in health economic modelling, where a particular parameter (or parameters)…
Joint longitudinal-survival models with time-dependent effects (non-proportional hazards)
In this post we’ll focus on how to model time-dependent effects (non-proportional hazards), specifically within a joint longitudinal-survival model. If this is your first time reading a little about joint models, check out our other posts on joint models on…
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