6 papers
A Bayesian adaptive enrichment design using aggregate historical data to inform individualized treatment recommendations
Lara Maleyeff, Shirin Golchi, Erica E. M. Moodie
Adaptive enrichment trials aim to identify and recruit participants most likely to benefit from treatment based on evolving biomarker evidence, with the goal of informing individua…
An Efficient Approach to Design Bayesian Platform Trials
Luke Hagar, Lara Maleyeff, Shirin Golchi +1
Platform trials evaluate multiple experimental treatments against a common control group (and/or against each other), which often reduces the trial duration and sample size. Bayesi…
The efficiencies of pilot feasibility trials in rare diseases using Bayesian methods
Lara Maleyeff, Valérie Leclair, Shirin Golchi +1
Pilot feasibility studies play a pivotal role in the development of clinical trials for rare diseases, where small populations and slow recruitment often threaten trial viability.…
Characterization of locally most split reliable graphs
Pablo Romero
A two-terminal graph is a graph equipped with two distinguished vertices, called terminals. Let be the set of all nonisomorphic connected simple two-terminal graphs on $n…
fkbma: An R Package for Detecting Tailoring Variables with Free-Knot B-Splines and Bayesian Model Averaging
Lara Maleyeff, Shirin Golchi, Erica E. M. Moodie
Precision medicine aims to optimize treatment by identifying patient subgroups most likely to benefit from specific interventions. To support this goal, we introduce fkbma, an R pa…
An adaptive enrichment design using Bayesian model averaging for selection and threshold-identification of tailoring variables
Lara Maleyeff, Shirin Golchi, Erica E. M. Moodie +1
Precision medicine stands as a transformative approach in healthcare, offering tailored treatments that can enhance patient outcomes and reduce healthcare costs. As understanding o…