Statistical programming grant winners 2020
Each year, a competition is run by the Statistics & Methodology Platform for statisticians in the CTU Network environment to develop code or programmes that will ultimately help improve clinical research and bring fresh solutions to persisting difficulties.
In 2020, Dr Marco Cattaneo from CTU Basel and Dr Arnaud Künzi from CTU Bern won the grants for the following statistical programming packages:
- “selcorr” by Dr Marco Cattaneo will be written in R. The package’s purpose is to correct the p value upwards after stepwise selection of variables for a multivariable regression analysis. The uncorrected p value is too optimistic because it does not account for the fact that the variables have been selected for goodness-of-fit out of a larger set of variables. The package should therefore help yielding p values and CIs (confidence intervals) that are more adequate.
- “sts_graph2” by Dr. Arnaud Künzi serves to conduct and visualise a landmark analysis in Stata. Landmark analyses are a popular observation method for comparing failure time that depend on group membership at the time of analysis. It is usually presented graphically using a Kaplan-Meier graph, supplemented by a table showing the risk population. Until now, landmark analysis in Stata has been very time-consuming, so a special, ready-to-use tool package is highly appreciated by the community.
Learn more about the CTU Network’s under Grants to foster open-access statistical tools further below on this page.