Clinical trials following the “gold standard” of random assignment frequently use independent lotteries to allocate patients to treatment and control arms. Unfortunately, independent assignment can generate treatment and control arms that are unbalanced (i.e. treatment and control populations with significantly different demographics). This is regrettable since other assignment methods such as matched pair designs ensure balance across arms while maintaining randomization and permitting inference. This paper seeks to measure the cost of imbalance with respect to gender in a sample of roughly 2000 clinical studies. We document significant imbalance: 25% of experiments have at least 26% more men in one treatment arm than in the other. In addition, clinical trials with greater imbalance have more dispersed treatment effects, indicating that imbalance reduces the informativeness of experiments. A simple structural model suggests that for a typical experiment, using a balanced random design could deliver informativeness gains equivalent to increasing the sample size by 18%.
Sign up to receive email alerts when we publish a new working paper.