Abstract
Menopause-associated thermoregulatory dysfunction can lead to symptoms such as hot flushes severely impairing quality of life of affected women. Treatment effects are often assessed by the ovariectomized rat model providing time series of tail skin temperature measurements in which circadian rhythms are a fundamental ingredient. In this work, a new statistical strategy is presented for analyzing such stochastic-dynamic data with the aim of detecting successful drugs in hot flush treatment. The circadian component is represented by a nonlinear dynamical system which is defined by the van der Pol equation and provides well-interpretable model parameters. Results regarding the statistical evaluation of these parameters are presented.