4 citations · 10 across the 23 of their papers we have counts for
24 papers
Frequentist-calibrated Bayesian group sequential design with dynamic borrowing
Francesco Mariani, Shirin Golchi, Stefania Gubbiotti +1
Bayesian analysis is increasingly used in clinical trials. However, assessment of the design with respect to the frequentist operating characteristics, such as type I error and pow…
Bayesian Design and Analysis of Precision Trials with Partial Borrowing
Shirin Golchi, Satoshi Morita
With the advancement of precision medicine there is an increasing need for design and analysis methods in clinical trials with the objective of investigating effect heterogeneity a…
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…
Bayesian Design of Experiments in the Presence of Nuisance Parameters
Shirin Golchi, Luke Hagar
Design of experiments has traditionally relied on the frequentist hypothesis testing framework where the optimal size of the experiment is specified as the minimum sample size that…
Identifying Treatment Effect Heterogeneity with Bayesian Hierarchical Adjustable Random Partition in Adaptive Enrichment Trials
Xianglin Zhao, Shirin Golchi, Jean-Philippe Gouin +1
Treatment effect heterogeneity refers to the systematic variation in treatment effects across subgroups. There is an increasing need for clinical trials that aim to investigate tre…
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.…
Classifying group actions on hyperbolic spaces
D. Osin, K. Oyakawa, A. Rapinchuk
For a given group , it is natural to ask whether one can classify all isometric -actions on Gromov hyperbolic spaces. We propose a formalization of this problem utilizing the…
A Precision Trial Case Study for Heterogeneous Treatment Effects in Obstructive Sleep Apnea
Lara Maleyeff, Shirin Golchi, Erica E. M. Moodie +1
Precision medicine tailors treatments to individual patient characteristics, which is especially valuable for conditions like obstructive sleep apnea (OSA), where treatment respons…
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…
Design of Bayesian Clinical Trials with Clustered Data
Luke Hagar, Shirin Golchi
In the design of clinical trials, it is essential to assess the design operating characteristics (e.g., power and the type I error rate). Common practice for the evaluation of oper…
Sparse two-stage Bayesian meta-analysis for individualized treatments
Junwei Shen, Erica E. M. Moodie, Shirin Golchi
Individualized treatment rules tailor treatments to patients based on clinical, demographic, and other characteristics. Estimation of individualized treatment rules requires the id…
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…
Bayesian Optimization for Identification of Optimal Biological Dose Combinations in Personalized Dose-Finding Trials
James Willard, Shirin Golchi, Erica EM Moodie
Early phase, personalized dose-finding trials for combination therapies seek to identify patient-specific optimal biological dose (OBD) combinations, which are defined as safe dose…
Bayesian Optimization for Personalized Dose-Finding Trials with Combination Therapies
James Willard, Shirin Golchi, Erica E. M. Moodie +2
Identification of optimal dose combinations in early phase dose-finding trials is challenging, due to the trade-off between precisely estimating the many parameters required to fle…
Estimating the Sampling Distribution of Posterior Decision Summaries in Bayesian Clinical Trials
Shirin Golchi, James Willard
Bayesian inference and the use of posterior or posterior predictive probabilities for decision making have become increasingly popular in clinical trials. The current practice in B…
Covariate Adjustment in Bayesian Adaptive Randomized Controlled Trials
James Willard, Shirin Golchi, Erica EM Moodie
In conventional randomized controlled trials, adjustment for baseline values of covariates known to be at least moderately associated with the outcome increases the power of the tr…
New designs for Bayesian adaptive cluster-randomized trials
Junwei Shen, Shirin Golchi, Erica E. M. Moodie +1
Adaptive approaches, allowing for more flexible trial design, have been proposed for individually randomized trials to save time or reduce sample size. However, adaptive designs fo…
Estimating Design Operating Characteristics in Bayesian Adaptive Clinical Trials
Shirin Golchi
Bayesian adaptive designs have gained popularity in all phases of clinical trials with numerous new developments in the past few decades. During the COVID-19 pandemic, the need to…
Use of Historical Individual Patient Data in Analysis of Clinical Trials
Shirin Golchi
Historical data from previous clinical trials, observational studies and health records may be utilized in analysis of clinical trials data to strengthen inference. Under the Bayes…
Monte Carlo based Designs for Constrained Domains
Shirin Golchi, Jason L. Loeppky
Space filling designs are central to studying complex systems in various areas of science. They are used for obtaining an overall understanding of the behaviour of the response ove…
A Bayesian Search for the Higgs Particle
Shirin Golchi, Richard Lockhart
The statistical procedure used in the search for the Higgs boson is investigated in this paper. A Bayesian hierarchical model is proposed that uses the information provided by the…
Sequentially Constrained Monte Carlo
Shirin Golchi, David A. Campbell
Constraints can be interpreted in a broad sense as any kind of explicit restriction over the parameters. While some constraints are defined directly on the parameter space, when th…
Monotone Function Estimation for Computer Experiments
Shirin Golchi, Derek R. Bingham, Hugh Chipman +1
In statistical modeling of computer experiments sometimes prior information is available about the underlying function. For example, the physical system simulated by the computer c…