The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
In a previous blog, we provided an overview of basic data structures in R. In this follow up piece, we will provide a snapshot of basic syntax in R for programmers who want to get up to speed in this increasingly important programming language.
R is on the rise in biopharma, and as we have previously discussed on the blog, it is now time for SAS programmers to get up to speedwith this popular and powerful programming language. Indeed, one of the advantages of R is its ability to integrate with other languages like C, C++, Python and SAS. Its strong graphical capabilities allow output in PDF, JPG, PNG, and SVG formats and table outputs for LaTeX and HTML. Importantly, as an open source resource, there is a strong community around R and extensive support for users in the form of forums like R-bloggers, StackOverflow and GitHub Repository
In this blog, we’ll provide an overview of R basic structures for programmers.
In the complex world of trial design and data analysis biostatisticians and data scientists need to ensure they are selecting and harnessing the best capabilities of the powerful software tools available to them. Particularly when non-standard approaches are required, this may mean using a combination of tools to come to the most appropriate solution for any task.
At the recent EARL conference, Cytel’s Aniruddha Deshmukh, Software Evangelist, discussed how R can be harnessed to extend and customize the powerful capabilities of East. Using R API , it’s possible to execute R code and manipulate R objects which are coded in other languages such as C/C++ and this approach has been used in East® to extend its features as well as customize simulations to meet any non-standard needs of a given clinical trial.
In this blog Aniruddha will take a techical look at R API and some of its key elements
Use of R is a hot topic among statisticians and programmers in the pharmaceutical industry. At the recent PhUSE conference in Barcelona there was a clear uplift in interest in the language and a number of sessions explored introductory principles and examples of how R can be used in practice. Cytel's Namrata Deshpande presented on the use of R beyond Statistics through a case study of the development of a user friendly tool deploying non-statistical packages in R to enable clinical decision making. The talk won first prize in the Trends and Technology track at the PhUSE conference. In this blog, we'll discuss some of the aspects presented and share Namrata's slides for download.