RAMPE: Randomisation Allocation Method Performance Evaluation

Session

When designing and conducting a randomised controlled trial, there are a variety of randomisation methods to choose from, but limited evidence on the performance of the methods under specific study designs. The RAMPE package contains 12 metrics designed to measure the balance and predictability of randomisation sequences in Stata. This will allow researchers to easily compare method performance using data that mirrors the specific trial that is being designed. Balance metrics: Measured both as the greatest imbalance observed throughout recruitment, and the final imbalance once the target sample size is achieved. groupimbalance: Measures the imbalance between the expected and observed ratio of participants in each treatment group. charimbalance: Measures the greatest imbalance observed across a set of covariates and the average imbalance across covariates. Predictability metrics: Measured as the proportion of correct guesses for a variety of prediction strategies. This is calculated for the whole sequence and assuming that recruiting sites only have information about previous allocations at their own site. alternation Recruiter assumes the next allocation is the one least recently allocated. backtheloser: Recruiter assumes the next allocation is the one with the fewest previous allocations. predbalance: Recruiter assumes the next allocation is the group with the smallest marginal total across randomisation covariates. In this talk, I will describe each of the developed metrics in more detail, discuss the interpretation of each metric and demonstrate with an example how this package can be used in practice.