We studied heart rate variability in rats by power scaling spectral analysis (PSSA), autoregressive modeling (AR), and detrended fluctuation analysis (DFA) and assessed stability by coefficient of variation (CV) between consecutive 6-hour epochs, and then (compared) cross-correlation among techniques. These same parameters were checked from baseline conditions through acute and chronic disease states (streptozotocin-induced diabetes) followed by therapeutic intervention (in-sulin). Cross-correlation between methods over the entire time period was DFA and PSSA (r=0.94), DFA and AR (r=0.81), AR and PSSA (r=0.77). Under baseline conditions, the scaling pa-rameter measured by DFA and PSSA and the HF component measured by AR fluctuated around an average value, but these fluctuations were different for the three methods. After diabetes in-duction, a strong correlation was found between the HF power and the short-term scaling pa-rameter. Despite their differences in methodology, DFA/PSSA assess changes in parasympathetic tone as detected by autoregressive modeling.