Stimulus-related oscillations are known to be closely linked to integrative processing in the brain. One research domain within which there has been tremendous interest in oscillatory mechanisms is in the integration of inputs across the widely separated sensory systems. Under the standard approach of assessing multisensory interactions in electrophysiological datasets, the event-related response to a multisensory stimulus is directly compared with the sum of the responses to its unisensory constituents when presented alone. When using methods like wavelet transformation or fast Fourier transformation to derive induced oscillatory signals, however, such linear operations are not appropriate. Here we introduce a simple bootstrapping procedure wherein the linear summation of single unisensory trials forms a distribution against which multisensory trials may be statistically compared, an approach that circumvents the issue of non-linearity when combining unisensory oscillatory responses. To test this approach we applied it to datasets from intracranial recordings in non-human primates and human scalp-recorded EEG, both derived from a simple audio-visual integration paradigm. Significant multisensory interactions were revealed in oscillatory activity centered at 15 and 20 Hz (the so-called beta band). Simulations of different levels of background noise further validated the results obtained by this method. By demonstrating super- and sub-additive effects, our analyses showed that this approach is a valuable metric for studying multisensory interactions reflected in induced oscillatory responses.