Line plots are very well suited for visually representing time-series. However, several difficulties arise when multivariate heterogeneous time-series data is displayed and compared visually. Especially, if the developments and trends of time-series of different units or value ranges need to be compared, a straightforward overlay could be visually misleading. To mitigate this, visualization pioneer Jacques Bertin presented a method called indexing that transforms data into comparable units for visual representation. In this paper, we want to provide empirical evidence for this method and present a comparative study of the three visual comparison methods linear scale with juxtaposition, log scale with superimposition and indexing. Although for task completion times, indexing only shows slight advantages, the results support the assumption that the indexing method enables the user to perform comparison tasks with a significantly lower error rate. Furthermore, a post-test questionnaire showed that the majority of the participants favour the indexing method over the two other comparison methods.