The log rank test is often used to test the hypothesis of equality for the survival functions of two treatment groups in a randomised controlled trial. Alongside this, trials often estimate the hazard ratio (HR) comparing the hazards of failure in the two groups. Typically the HR is estimated by fitting Cox’s proportional hazards model, and a 95% confidence interval is used to indicate the precision of the estimated HR.
Multiple imputation for informative censoring R package
Yesterday the Advanced Analytics Centre at AstraZeneca publicly released the InformativeCensoring package for R, on GitHub. Standard survival or time to event analysis methods assume that censoring is uninformative – that is that the hazard of failure in those subjects at risk at a given time and who have not yet failed or been censored, is the same as the hazard at that time in those who have been censored (with regression modelling, this assumption is somewhat relaxed).
Estimands and assumptions in clinical trials
Today I listened to a great Royal Statistical Society webinar, with Alan Phillips and Peter Diggle (current RSS president) presenting. The topic was a particularly hot one in the clinical trials world right now, namely estimands.
Alan’s presentation gave an excellent overview of the work of a PSI/EFSPI special interest group on estimands. Topics discussed included defining exactly what is meant by an estimand, whether there should be a standardised set of estimands which could be used across trials conducted in different disciplines, and what the estimand discussion means in terms of implementation and statistical analysis.