R is a very powerful tool for performing statistical programming, but has had a lower uptake in the life sciences when compared to SAS. As a result, many of the packages created for R are not focused on the type of tasks Statistical Programmers do. In this talk I introduce several packages and in house training we are developing to aid regulatory outputs. The R packages include rcompare, a package to allow comparison of datasets, analogous to proc compare in SAS, and r4spa which allows outputs to be in the correct format for production. Each package solves a problem particular to the life sciences, and is intended to improve uptake of R usage within the industry. Similarly, to the R packages, the training is focused on providing examples of actual work, so that users of the training will be able to immediately apply their knowledge.
Kieran Martin
Roche
R4SPA: R Packages and Training to enable Statistical Programming in R
R is a very powerful tool for performing statistical programming, but has had a lower uptake in the life sciences when compared to SAS. As a result, many of the packages created for R are not focused on the type of tasks Statistical Programmers do. In this talk I introduce several packages and in house training we are developing to aid regulatory outputs. The R packages include rcompare, a package to allow comparison of datasets, analogous to proc compare in SAS, and r4spa which allows outputs to be in the correct format for production. Each package solves a problem particular to the life sciences, and is intended to improve uptake of R usage within the industry. Similarly, to the R packages, the training is focused on providing examples of actual work, so that users of the training will be able to immediately apply their knowledge.