Here, we compare the performance of a spectrum of MSER methods which apply increasingly rigorous techniques to account for correlation. These include the original MSER method and a method which is effectively identical to Chodera's heuristic. To rigorously assess their performance, we test these methods on synthetic data modelled on long absolute binding free energy calculations for a variety of protein-ligand complexes. This work complements the recent study of Oliveira et al. by testing a wide range of MSER methods and quantitatively assessing their performance. We limit ourselves to the analysis of single runs, but note that truncation point selection and uncertainty quantification based on an ensemble of repeat runs are likely to be more robust, if more expensive. All methods discussed are implemented in the open-source Python package RED (Robust Equilibration Detection, github.com/fjclark/red, where equilibration is used in the sense of finding the optimal truncation point). This provides alternatives for the PyMBAR timeseries "detect equilibration" function. 2 Theory