<p>PK-QTc analyses are an integral part of drug development programs. These analyses are often based on phase I study data, and the question may be asked whether the design of these phase I studies has an impact on the precision of the corresponding PK-QT analysis. More precisely, we are interested whether one can increase the power of such analyses when using interleaved ascending dose designs rather than parallel group ascending dose designs. Based on a simulation study, previous authors have concluded that this is the case. Their conclusions, however, are based on assumptions regarding the magnitude of the random effect variances, and on a very specific set-up of their simulation study. In this paper we provide a study re-analysis of historical QTc data. The resulting estimates of these random effect variances are much smaller than those used by the previous authors. We also propose a simulation set-up that adequately mimics the data generation process and the correlation between the primary endpoint change from baseline and the covariate baseline. We present a simulation study using the revised simulation set-up and random effect variances as observed in our study re-analysis. We did not find major differences in power between the different designs when the number of observations is the same. We also provide a justification based on causal analysis why we think our simulation set-up is more adequate for situations when change from baseline is the primary endpoint, specifically when baseline is used as a covariate.</p>