Health technology assessment (HTA) is the primary tool used by healthcare decision makers when evaluating novel pharmaceuticals and other technologies within healthcare systems. HTAs use a variety of evidence to evaluate new technologies including statistical analyses and cost-effectiveness analysis (CEA).
R is a free program designed for statistical analysis and graphical techniques. Because R is designed to display and process complex data, it is seen as an alternative to less efficient and less powerful software such as Microsoft Excel. For these reasons, the popularity of R has increased in the last decade and is starting to be used within HTA submissions.
By the end of this full day course, attendees will be able to proficiently navigate the R program as well as import/export their own data from a variety of data sources.
Participants will learn the skills required to explore their data as well as produce summary statistics and create interesting graphics using reproducible R scripts. The course will also provide detailed advice on how to manipulate data in R ready for use in efficient statistical analyses. We will also discuss the use of R in evidence synthesis and CEA with some example models covering several disease areas demonstrated.
The course is designed for beginners and no prior R knowledge will be assumed.