Heart rate variability (HRV) and baroreceptor sensitivity (BRS) quantify autonomic variability in heart pacing and the autonomic response to blood pressure changes respectively. By necessity, the signals used to calculate HRV and BRS (systolic blood pressure (SBP) and RR interval) have one data point every cardiac cycle. Due to inherent variability in heart rate, these are non-uniformly sampled data. A number of calculation methods exist that adjust for non-uniform sampled signals. This study compared frequency domain methods of HRV and BRS calculation to ascertain whether more complex methods resulted in different results to simpler methods. Wistar rats (n=10), and rats with induced diabetes (n=8) were anesthetized and SBP and RR interval measured for a period of approximately 5 minutes. This data were analyzed using the sequence technique (for BRS), fast Fourier transform (FFT), non-uniform discrete Fourier transform (NDFT) and an extended Lomb-Scargle Periodogram (LSP). There were small but significant differences in NDFT from LSP technique for both BRS in the low frequency range (p=0.005) and HRV in the high frequency range (p=0.001). The NDFT technique was also significantly different to FFT technique for BRS in the low frequency range (p=0.023). All other methods were not statistically different. However, all techniques showed the same results comparing diabetic to control rats. This study shows more complex methods that correct for the non-uniformity of the sampling have significant differences but those differences are small to the point of not altering findings associated with HRV or BRS.