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Mitchell Aaron Schepps, Weng Kee Wong, Matt Austin & Volodymyr Anisimov. (2024) Optimizing Patient Recruitment in Global Clinical Trials using Nature-Inspired Metaheuristics. Statistics in Biopharmaceutical Research 0:0, pages 1-15.
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Vladimir Anisimov & Matthew Austin. (2020) Centralized statistical monitoring of clinical trial enrollment performance. Communications in Statistics: Case Studies, Data Analysis and Applications 6:4, pages 392-410.
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Dejian Lai, Qiang Zhang, Jose-Miguel Yamal, Paula T. Einhorn & Barry R. Davis. (2017) Conditional moving linear regression: Modeling the recruitment process for ALLHAT. Communications in Statistics - Theory and Methods 46:18, pages 8943-8951.
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Vladimir V. Anisimov. (2016) Predictive Hierarchic Modeling of Operational Characteristics in Clinical Trials. Communications in Statistics - Simulation and Computation 45:5, pages 1477-1488.
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Articles from other publishers (36)
Philip Heesen & Malgorzata Roos. (2024) Freely accessible software for recruitment prediction and recruitment monitoring of clinical trials: A systematic review. Contemporary Clinical Trials Communications 39, pages 101298.
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Oleksandr Sverdlov, Yevgen Ryeznik, Volodymyr Anisimov, Olga M. Kuznetsova, Ruth Knight, Kerstine Carter, Sonja Drescher & Wenle Zhao. (2024) Selecting a randomization method for a multi-center clinical trial with stochastic recruitment considerations. BMC Medical Research Methodology 24:1.
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Mengjia Yu, Sheng Zhong, Yunzhao Xing & Li Wang. (2023) Enrollment Forecast for Clinical Trials at the Planning Phase with Study-Level Historical Data. Therapeutic Innovation & Regulatory Science 58:1, pages 42-52.
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Virginia B. Shipes, Caitlyn Meinzer, Bethany J. Wolf, Hong Li, Mathew J. Carpenter, Hooman Kamel & Renee H. Martin. (2023)
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Armando Turchetta, Nicolas Savy, David A. Stephens, Erica E.M. Moodie & Marina B. Klein. (2023) A time‐dependent Poisson‐Gamma model for recruitment forecasting in multicenter studies. Statistics in Medicine 42:23, pages 4193-4206.
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Volodymyr Anisimov. (2023) An Analytic Methodology for Forecasting Patient Enrolment Performance in Multicentre Clinical Trials: Forecasting Patient Enrolment Performance in Clinical Trials. An Analytic Methodology for Forecasting Patient Enrolment Performance in Multicentre Clinical Trials: Forecasting Patient Enrolment Performance in Clinical Trials.
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Rachael Mountain & Chris Sherlock. (2021) Recruitment prediction for multicenter clinical trials based on a hierarchical Poisson–gamma model: Asymptotic analysis and improved intervals. Biometrics 78:2, pages 636-648.
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Cameron Bieganek, Constantin Aliferis & Sisi Ma. (2022) Prediction of clinical trial enrollment rates. PLOS ONE 17:2, pages e0263193.
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Vladimir Anisimov & Matthew Austin. 2022. Stochastic Processes, Statistical Methods, and Engineering Mathematics. Stochastic Processes, Statistical Methods, and Engineering Mathematics
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Ruan Spies, Nandi Siegfried, Bronwyn Myers & Sara S. Grobbelaar. (2021) Concept and development of an interactive tool for trial recruitment planning and management. Trials 22:1.
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Michael Lefew, Anh Ninh & Vladimir Anisimov. (2020) End-to-End Drug Supply Management in Multicenter Trials. Methodology and Computing in Applied Probability 23:3, pages 695-709.
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Ryunosuke Machida, Yosuke Fujii & Takashi Sozu. (2021) Predicting study duration in clinical trials with a time‐to‐event endpoint. Statistics in Medicine 40:10, pages 2413-2421.
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Mahesh Ramanan, Laurent Billot, Dorrilyn Rajbhandari, John Myburgh, Simon Finfer, Rinaldo Bellomo & Balasubramanian Venkatesh. (2020) Does asymmetry in patient recruitment in large critical care trials follow the Pareto principle?. Trials 21:1.
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Junhao Liu, Jo Wick, Yu Jiang, Matthew Mayo & Byron Gajewski. (2020) Bayesian accrual modeling and prediction in multicenter clinical trials with varying center activation times. Pharmaceutical Statistics 19:5, pages 692-709.
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Vladimir V. Anisimov. 2020. Quantitative Methods in Pharmaceutical Research and Development. Quantitative Methods in Pharmaceutical Research and Development
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Linda E. Carlson, Utkarsh B. Subnis, Katherine‐Anne L. Piedalue, James Vallerand, Michael Speca, Sasha Lupichuk, Patricia Tang, Peter Faris & Ruth Q. Wolever. (2019) The ONE‐MIND Study: Rationale and protocol for assessing the effects of ONlinE MINDfulness‐based cancer recovery for the prevention of fatigue and other common side effects during chemotherapy. European Journal of Cancer Care 28:4.
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Fang‐Shu Ou, Martin Heller & Qian Shi. (2019) Milestone prediction for time‐to‐event endpoint monitoring in clinical trials. Pharmaceutical Statistics 18:4, pages 433-446.
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Lisa V Hampson, Paula R Williamson, Martin J Wilby & Thomas Jaki. (2017) A framework for prospectively defining progression rules for internal pilot studies monitoring recruitment. Statistical Methods in Medical Research 27:12, pages 3612-3627.
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Nathan Minois, Stéphanie Savy, Valérie Lauwers-Cances, Sandrine Andrieu & Nicolas Savy. (2017) How to deal with the Poisson-gamma model to forecast patients' recruitment in clinical trials when there are pauses in recruitment dynamic?. Contemporary Clinical Trials Communications 5, pages 144-152.
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Vladimir V. Anisimov. (2016) Discussion on the paper “Real-Time Prediction of Clinical Trial Enrollment and Event Counts: A Review”, by DF Heitjan, Z Ge, and GS Ying. Contemporary Clinical Trials 46, pages 7-10.
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