Diagity - An Inovia Bio Advanced RWE Study Design Visualization tool

Link copied to clipboard

If you would like to remove the Inovia Bio watermark or a consultation with our expert RWE team in study designs by clicking the button bellow:

Inovia Bio (https://www.inovia.bio/), Diagity RWE Study Designer London, UK, Department of Advanced Drug Development Innovation 2024. Available from https://diagity.inovia.bio/(link is external). (Accessed [INSERT DATE])

This tool is based upon the great work of the following papers:

1. Schneeweiss S, Rassen JA, Brown JS, Rothman KJ, Happe L, Arlett P, et al. Graphical Depiction of Longitudinal Study Designs in Health Care Databases. Ann Intern Med. 2019 Mar 19;170(6):398.
2. Suissa S. Immortal time bias in pharmaco-epidemiology. Am J Epidemiol. 2008 Feb 15;167(4):492–9.
3. R Core Team. R: A Language and Environment for Statistical Computing [Internet]. Vienna, Austria: R Foundation for Statistical Computing; 2018. Available from: https://www.R-project.org/
4. Chang W, Cheng J, Allaire JJ, Xie Y, McPherson J. shiny: Web Application Framework for R [Internet]. 2019. Available from: https://CRAN.R-project.org/package=shiny
5. Wickham H. ggplot2: Elegant Graphics for Data Analysis [Internet]. Springer-Verlag New York; 2016. Available from: https://ggplot2.tidyverse.org