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20172021
most citedUsing simulation studies to evaluate statistical methods

1.4k citations · 1.4k across the 11 of their papers we have counts for

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7 papers · 1 filter

stat.ME2021

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…

stat.ME2020

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…

stat.ME2018★ 18 cited

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…

stat.ME2018★ 32 cited

Mixed effects models for healthcare longitudinal data with an informative visiting process: a Monte Carlo simulation study

Alessandro Gasparini, Keith R. Abrams, Jessica K. Barrett +4

Electronic health records are being increasingly used in medical research to answer more relevant and detailed clinical questions; however, they pose new and significant methodolog…

stat.ME2018

Joint longitudinal and time-to-event models for multilevel hierarchical data

Samuel L. Brilleman, Michael J. Crowther, Margarita Moreno-Betancur +6

Joint modelling of longitudinal and time-to-event data has received much attention recently. Increasingly, extensions to standard joint modelling approaches are being proposed to h…

stat.ME2017★ 1.4k cited

Using simulation studies to evaluate statistical methods

Tim P Morris, Ian R White, Michael J Crowther

Simulation studies are computer experiments that involve creating data by pseudorandom sampling. The key strength of simulation studies is the ability to understand the behaviour o…

stat.ME2017★ 17 cited

Extended multivariate generalised linear and non-linear mixed effects models

Michael J. Crowther

Multivariate data occurs in a wide range of fields, with ever more flexible model specifications being proposed, often within a multivariate generalised linear mixed effects (MGLME…