Interests
- Computational methods for design and analysis of adaptive clinical trials
- Bayesian methods for design/analysis of clinical trials
- Bayesian hypothesis testing and frequency-calibrated Bayesian procedures
Team
PhD
- James J. Willard (2020-present) (with Erica Moodie)
- Junwei Shen (2020-present) (with Erica Moodie)
- Tasneem Fatima Alam (2021-present) (with Alexandra Schmidt)
- Xianglin Zhao (2022 – present)
MSc
- Lily Chafetz (with Alexandra Schmidt)
Publications
J. Shen*, S. Golchi, E. E. M. Moodie, D. Benrimoh. (2022) New Designs for Bayesian Adaptive Cluster-Randomized Trials. Stat. In press.
S. Golchi, J. J. Willard*, E. Pullenayegum, D. G. Bassani, L. G. Pell, K. Thorlund, and D. E. Roth. (2022) A Bayesian Adaptive Design for Clinical Trials of Rare Efficacy Outcomes with Multiple Definitions. Clinical Trials. In press.
S. Golchi. (2021) Estimating design operating characteristics in Bayesian adaptive clinical trials. Canadian Journal of Statistics. Vol. 50, No. 2, pp. 417–436. https://doi.org/10.1002/cjs.11699
S. Golchi, J. Fu, X. Liu, E. Yu, R. Forghani, S. Bhatnagar. (2021) Sparse Bayesian Predictive Modelling of Tumor Response Using Radiomic Feature. Stat. Vol. 11, No. 1. https://doi.org/10.1002/sta4.4509
M. Miocevic, S. Golchi. (2021) Bayesian mediation analysis with power prior distributions. Multivariate Behavioral Research. doi:10.1080/00273171.2021.1935202
S. Golchi, K. Thorlund. (2020) Sequential Monte Carlo for Response Adaptive Randomized Trials. Biostatistics. Vol. 21, No. 2, pp. 287–301. https://doi.org/10.1093/biostatistics/kxy048
L. Dron, S. Golchi, G. Hsu, K. Thorlund. (2019). Minimizing control group allocation in randomized trials using dynamic borrowing of external control data: an application to second line therapy for non-small cell lung cancer. Contemporary Clinical Trials Communications. 16:100446. doi:http://10.1016/j.conctc.2019.100446
K. Thorlund, S. Golchi, J. Haggstrom, E. Mills. (2019). Highly Efficient Clinical Trials Simulator (HECT): Software application for planning and simulating platform adaptive trials. Gates Open Research. 3:780. doi:http://10.12688/gatesopenres.12912.2
S. Golchi and R. Lockhart. (2018) A Frequency-Calibrated Bayesian Search for New Particles. Annals of Applied Statistics. 12:3, 1939-1968. https://doi.org/10.1214/18-AOAS1138
S. Golchi (2018) Informative Priors in Bayesian Inference and Computation. Statistical Analysis and Data Mining: The ASA Data Science Journal. https://doi.org/10.1002/sam.11371
K. Thorlund, S. Golchi, E. Mills. (2017) Bayesian Adaptive Clinical Trials of Combination Treatments. Contemporary Clinical Trials Communications. 8, 227-233.
S. Golchi and D.A. Campbell (2016). Sequentially Constrained Monte Carlo. Computational Statistics and Data Analysis. 97, 98-113.
S. Golchi, D. Bingham, H. Chipman, and D.A. Campbell (2015). Monotone Emulation of Computer Experiments. SIAM/ASA Journal on Uncertainty Quantification. 3:1, 370-392.