5 papers
A continuous-time Markov chain framework for population size estimation from multi-list data: accounting for absorbing lists and asymmetric interactions
Ophélie Schaller, Andrew Titman, Rachel McCrea
We introduce a continuous-time Markov chain framework for estimating population size from multi-list data, which allows directional interactions to be modelled and can accommodate…
Comparison of Estimators for Multi-State Models in Potentially Non-Markov Processes
Carolin Drenda, Dennis Dobler, Merle Munko +1
Various estimators for modelling the transition probabilities in multi-state models have been proposed, e.g., the Aalen-Johansen estimator, the landmark Aalen-Johansen estimator, a…
A Seamless Phase I/II Platform Design with a Time-To-Event Efficacy Endpoint for Potential COVID-19 Therapies
Thomas Jaki, Helen Barnett, Andrew Titman +1
In the search for effective treatments for COVID-19, initial emphasis has been on re-purposed treatments. To maximise the chances of finding successful treatments, novel treatments…
Subgroup analysis of treatment effects for misclassified biomarkers with time-to-event data
Fang Wan, Andrew C. Titman, Thomas F. Jaki
Analysing subgroups defined by biomarkers is of increasing importance in clinical research. In some situations the biomarker is subject to misclassification error, meaning the true…
Time-dynamic inference for non-Markov transition probabilities under independent right-censoring
Dennis Dobler, Andrew C. Titman
In this article, weak convergence of the general non-Markov state transition probability estimator by Titman (2015) is established which, up to now, has not been verified yet for o…