A Bayesian hierarchical approach for multiple outcomes in routinely collected healthcare data-Reference-Cited by-同舟云学术

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A Bayesian hierarchical approach for multiple outcomes in routinely collected healthcare data

Published:2020-05-07 Issue:20 Volume:39 Page:2639-2654
ISSN:0277-6715
Container-title:Statistics in Medicine
language:en
Short-container-title:Statistics in Medicine

Author:

Carragher Raymond¹²³^ORCID,Mueller Tanja¹,Bennie Marion¹⁴,Robertson Chris²⁵

Affiliation:

1. Strathclyde Institute of Pharmacy and Biomedical Sciences University of Strathclyde Glasgow UK

2. Department of Mathematics and Statistics University of Strathclyde Glasgow UK

3. Health Data Research (UK) University of Strathclyde Glasgow UK

4. Public Health and Intelligence Strategic Business Unit NHS National Services Scotland Glasgow UK

5. Health Protection Scotland NHS National Services Scotland Glasgow UK

Publisher

Wiley

Subject

Statistics and Probability,Epidemiology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/sim.8563

Reference27 articles.

1. Fundamentals of Clinical Trials

2. Comparative safety and effectiveness of direct oral anticoagulants in patients with atrial fibrillation in clinical practice in Scotland

3. Accounting for Multiplicity in the Evaluation of “Signals” Obtained by Data Mining from Spontaneous Report Adverse Event Databases

4. Bayesian Data Mining in Large Frequency Tables, with an Application to the FDA Spontaneous Reporting System

5. A Bayesian neural network method for adverse drug reaction signal generation

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Assessing safety at the end of clinical trials using system organ classes: A case and comparative study;Pharmaceutical Statistics;2021-06-24

2. c212: An R Package for the Detection of Safety Signals in Clinical Trials Using Body-Systems (System Organ Classes);Journal of Open Source Software;2020-12-04

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