Explicitly modeling underlying relationships between a survival endpoint and processes that
generate longitudinal measured or reported outcomes potentially could improve the …

Simulation studies are computer experiments that involve creating data by pseudo‐random
sampling. A key strength of simulation studies is the ability to understand the behavior of …

Background There is substantial interest in the adaptation and application of so-called
machine learning approaches to prognostic modelling of censored time-to-event data …

Simulation studies are conducted to assess the performance of current and novel statistical
models in pre‐defined scenarios. It is often desirable that chosen simulation scenarios …

If interest lies in reporting absolute measures of risk from time-to-event data then obtaining
an appropriate approximation to the shape of the underlying hazard function is vital. It has …

The joint modeling of longitudinal and survival data has received remarkable attention in the
methodological literature over the past decade; however, the availability of software to …

Multistate models are increasingly being used to model complex disease profiles. By
modelling transitions between disease states, accounting for competing events at each …

Background. Treatment switching commonly occurs in clinical trials of novel interventions in
the advanced or metastatic cancer setting. However, methods to adjust for switching have …

Objective To compare 10 year revision rates for frequently used types of primary total hip
replacement to inform setting of a new benchmark rate in England and Wales that will be of …

Multilevel mixed effects survival models are used in the analysis of clustered survival data,
such as repeated events, multicenter clinical trials, and individual participant data (IPD) meta …