Statistical modeling and prediction of clinical trial recruitment-Reference-Cited by-同舟云学术

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Statistical modeling and prediction of clinical trial recruitment

Published:2018-11-08 Issue:6 Volume:38 Page:945-955
ISSN:0277-6715
Container-title:Statistics in Medicine
language:en
Short-container-title:Statistics in Medicine

Author:

Lan Yu¹²,Tang Gong³⁴,Heitjan Daniel F.¹⁵^ORCID

Affiliation:

1. Department of Statistical Science Southern Methodist University Dallas Texas

2. Department of Biostatistics and Programming Sanofi Bridgewater New Jersey

3. Department of Biostatistics University of Pittsburgh Pittsburgh Pennsylvania

4. NRG Oncology Philadelphia Pennsylvania

5. Department of Clinical Sciences University of Texas Southwestern Medical Center Dallas Texas

Funder

U.S. Public Health Service

Publisher

Wiley

Subject

Statistics and Probability,Epidemiology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/sim.8036

Reference16 articles.

1. Some controversies in planning and analysing multi-centre trials

2. Interim recruitment goals in clinical trials

3. Predicting accrual in clinical trials with Bayesian posterior predictive distributions

4. Modelling, prediction and adaptive adjustment of recruitment in multicentre trials

5. Stochastic modeling and prediction for accrual in clinical trials

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1. The time-dependent Poisson-gamma model in practice: Recruitment forecasting in HIV trials;Contemporary Clinical Trials;2024-09

2. Freely accessible software for recruitment prediction and recruitment monitoring of clinical trials: A systematic review;Contemporary Clinical Trials Communications;2024-06

3. Designing a phase‐III time‐to‐event clinical trial using a modified sample size formula and Poisson‐Gamma model for subject accrual that accounts for the lag in site initiation using the PERT distribution;Statistics in Medicine;2023-11-05

4. Enrollment forecast for clinical trials at the portfolio planning phase based on site‐level historical data;Pharmaceutical Statistics;2023-10-23

5. Enrollment Forecast for Clinical Trials at the Planning Phase with Study-Level Historical Data;Therapeutic Innovation & Regulatory Science;2023-09-15

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