17 citations · 18 across the 4 of their papers we have counts for
10 papers
Simulating time-to-event data from parametric distributions, custom distributions, competing risk models and general multi-state models
Michael J. Crowther
In this paper I describe some substantial extensions to the survsim command for simulating survival data. survsim can now simulate survival data from a parametric distribution, a c…
Assessing and relaxing the Markov assumption in the illness-death model
Jonathan Broomfield, Caroline E. Weibull, Michael J. Crowther
Multi-state survival analysis considers several potential events of interest along a disease pathway. Such analyses are crucial to model complex patient trajectories and are increa…
A multi-state model incorporating estimation of excess hazards and multiple time scales
Caroline E. Weibull, Paul C. Lambert, Sandra Eloranta +3
As cancer patient survival improves, late effects from treatment are becoming the next clinical challenge. Chemotherapy and radiotherapy, for example, potentially increase the risk…
merlin: An R package for Mixed Effects Regression for Linear, Nonlinear and User-defined models
Emma C. Martin, Alessandro Gasparini, Michael J. Crowther
The R package merlin performs flexible joint modelling of hierarchical multi-outcome data. Increasingly, multiple longitudinal biomarker measurements, possibly censored time-to-eve…
INTEREST: INteractive Tool for Exploring REsults from Simulation sTudies
Alessandro Gasparini, Tim P. Morris, Michael J. Crowther
Simulation studies allow us to explore the properties of statistical methods. They provide a powerful tool with a multiplicity of aims; among others: evaluating and comparing new o…
Impact of model misspecification in shared frailty survival models
Alessandro Gasparini, Mark S. Clements, Keith R. Abrams +1
Survival models incorporating random effects to account for unmeasured heterogeneity are being increasingly used in biostatistical and applied research. Specifically, unmeasured co…