RRApp, a robust randomization app, for clinical and translational research
| Autor: | Emma K. T. Benn, Chengcheng Tu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Scheme (programming language)
Randomization 020205 medical informatics Electronic data capture Computer science media_common.quotation_subject Research Methods and Technology biostatistics Translational research 02 engineering and technology randomization Machine learning computer.software_genre law.invention 03 medical and health sciences 0302 clinical medicine Clinical trials Randomized controlled trial law Special Communication 0202 electrical engineering electronic engineering information engineering reproducibility media_common computer.programming_language Selection bias 030219 obstetrics & reproductive medicine business.industry General Medicine 3. Good health Stratified sampling Clinical trial Artificial intelligence business computer RCT |
| Zdroj: | Journal of Clinical and Translational Science |
| ISSN: | 2059-8661 |
| Popis: | While junior clinical researchers at academic medical institutions across the US often desire to be actively engaged in randomized-clinical trials, they often lack adequate resources and research capacity to design and implement them. This insufficiency hinders their ability to generate a rigorous randomization scheme to minimize selection bias and yield comparable groups. Moreover, there are limited online user-friendly randomization tools. Thus, we developed a free robust randomization app (RRApp). RRApp incorporates 6 major randomization techniques: simple randomization, stratified randomization, block randomization, permuted block randomization, stratified block randomization, and stratified permuted block randomization. The design phase has been completed, including robust server scripts and a straightforward user-interface using the “shiny” package in R. Randomization schemes generated in RRApp can be input directly into the Research Electronic Data Capture (REDCap) system. RRApp has been evaluated by biostatisticians and junior clinical faculty at the Icahn School of Medicine at Mount Sinai. Constructive feedback regarding the quality and functionality of RRApp was also provided by attendees of the 2016 Association for Clinical and Translational Statisticians Annual Meeting. RRApp aims to educate early stage clinical trialists about the importance of randomization, while simultaneously assisting them, in a user-friendly fashion, to generate reproducible randomization schemes. |
| Databáze: | OpenAIRE |
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