Inference from traditional historical controls, i.e. comparing a new treatment in a current series of patients with an old treatment in a previous series of patients, may be subject to a strong selection bias. To avoid this bias, Baker and Lindeman (1994) proposed the paired availability design. By applying this methodology to estimate the effect of epidural analgesia on the probability of Cesarean section, we made two important contributions with the current study. First, we generalized the methodology to include different types of availability and multiple time periods. Second, we investigated how well the paired availability design reduced selection bias by comparing results to those from a meta-analysis of randomized trials and a multivariate analysis of concurrent controls. The confidence interval from the paired availability approach differed considerably from that of the multivariate analysis of concurrent controls but was similar to that from the meta-analysis of randomized trials. Because we believe the multivariate analysis of concurrent controls omitted an important predictor and the meta-analysis of randomized trials was the gold standard for inference, we concluded that the paired availability design did, in fact, reduce selection bias.