The primary goal of this paper is to demonstrate the application of a relatively esoteric and interdisciplinary technique, called spectral analysis, to dyadic social sciences data. Spectral analysis is an analytical and statistical technique, commonly used in engineering, that allows times series data to be analyzed for the presence of significant regular/periodic fluctuations/oscillations. These periodic fluctuations are reflected in the frequency domain as amplitude or energy peaks at certain frequencies. Furthermore, a Magnitude Squared Coherence analysis may be used to interrogate more than one time series concurrently in order to establish the degree of frequency domain correlation between the two series, as well to establish the phase (lead/lag) relationship between the coherent frequency components. In order to demonstrate the application of spectral analysis, the current study utilizes a secondary dyadic dataset comprising 30 daily reports of perceived sexual desire for 65 couples. The secondary goal of this paper is to establish a) whether there is significant periodic fluctuation in perceived levels of sexual desire for men and/or women, and at which specific frequencies, and b) how much correlation or `cross-spectral coherence' there is between partners' sexual desire within the dyads, and c) what the phase lead-lag relationship is between the partners at any of the identified frequency components. Sexual desire was found to have significant periodic components for both men and women, with a fluctuation of once per month being the most common frequency component across the groups of individuals under analysis. Mathematical models are presented in order to describe and illustrate these principal fluctuations. Partners in couples, on average, were found to fluctuate together at a number of identified frequencies, and the phase lead/lag relationships of these frequencies are presented.