Despite the fact that the traditional transfer path analysis (TPA) is a very well-known method, it has not yet become a standard tool for the railway industry. One reason is certainly the time-consuming effort required for determining the TFs and the source quantities such as the operational forces and volume velocities. The operational transfer path analysis (OTPA) is a method, which derives the transfer functions (TF) with a so-called "cross-talk-cancellation" (CTC) technique directly from the operational data. Therefore, it is much faster and more effective than the traditional TPA. The application of the OTPA is illustrated by an investigation on a meter-gauge multiple-unit from Stadler Rail. A dominant sound path could be identified. As the CTC technique derives the TFs from the operational data, the captured operational conditions and the chosen reference signals become crucial. In order to assess the influence of the correlation between the reference signals, that effect is studied in this paper by means of several test cases. For this purpose, reference signals of test data were filtered with randomly chosen TFs and added to a virtual total sound pressure. Then, the generated test cases were analyzed using the CTC technique to reversely calculate the TFs from the reference signals and the virtual sound pressure. As the test cases were generated without cross-talk, the CTC results have to be identical to the TF used generating the test case. By comparing the TFs, the applicability of the CTC technique on the generated test data was examined. The first two test cases deal with 100% uncorrelated and 100% correlated reference signals. The cases show that the CTC technique can estimate the TFs precisely if the reference signals are uncorrelated. If the reference signals are 100% correlated, the TFs become less accurate. A further test was conducted using the experimental data from the presented OTPA example to assess the effect of typically correlated reference signals on the estimated TFs. For the investigated example, it could be shown that for realistic correlations, that are in the range from 0% up to about 90%, the CTC technique could exactly estimate the TFs.