International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 6 November-December 2024 Submit your research before last 3 days of December to publish your research paper in the issue of November-December.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 6 Issue 6
November-December 2024

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

Adaptive Clinical Trials: Implementing Dynamic Data Analysis in R Shiny

Author(s) Arvind Uttiramerur
Country USA
Abstract Adaptive clinical trials represent a transformative approach in clinical research, allowing for flexibility in trial design based on accumulating data. This methodology enhances the ability to make timely adjustments to various trial parameters, such as sample size, treatment regimens, or endpoints, ultimately improving the efficiency and efficacy of clinical investigations. The significance of dynamic data analysis lies in its capacity to facilitate real-time monitoring and decision-making throughout the trial lifecycle. Implementing dynamic data analysis using R Shiny empowers researchers to visualize and interpret complex datasets interactively, enabling stakeholders to make informed decisions promptly. This white paper explores the integration of R Shiny in adaptive clinical trials, highlighting its role in enhancing data analysis, visualization, and reporting. A case study demonstrates how R Shiny can facilitate real-time data visualization, enabling researchers to make informed decisions regarding trial adaptations. Key features of R Shiny, including user-friendly interfaces and interactive graphics, are discussed alongside challenges and solutions in adaptive trial design. The findings suggest that R Shiny is a valuable tool for improving the responsiveness and effectiveness of clinical trials.
Keywords Adaptive Clinical Trials, Dynamic Data Analysis, R Shiny, Real-Time Data Visualization, Clinical Trial Design, Data-Driven Decision Making.
Field Lainnya
Published In Volume 6, Issue 3, May-June 2024
Published On 2024-06-25
Cite This Adaptive Clinical Trials: Implementing Dynamic Data Analysis in R Shiny - Arvind Uttiramerur - IJFMR Volume 6, Issue 3, May-June 2024. DOI 10.36948/ijfmr.2024.v06i03.23859
DOI https://doi.org/10.36948/ijfmr.2024.v06i03.23859
Short DOI https://doi.org/g8k5vp
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 6 Isu 6Cover Page Vol 6 Isu 5Cover Page Vol 6 Isu 4

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9898-5948-55 editor@ijfmr.com