Gorr et al. [ 40] used a global clock approach to estimate divergence times within reptiles (including Aves).
PMU data are derived from waveform samples, time tagged using a global positioning system (GPS) clock, and typically transmitted from local substations or generating stations to control centers at 20 to 60 frames per second [16, 17, 18, 19, 20].
We also estimated the power of IIV, derived from MMSE, Clock Drawing, and ADAS, to explain variability in change in overall cognitive functioning using a global clinical measure, the Clinical Dementia Rating (CDR, [29]) sum of boxes.
Divergence time estimation was also conducted using a strict global clock assumption in BEAST, in order to get a more reasonable sense of the variability in divergence times for horse lineages.
Prüser and Mossakowski [ 3] used a strict global clock method and the opening of the Gibraltar Strait at the end of the Miocene to calibrate hypothetic vicariance events between Iberian and North African populations of Carabus species.
Quartets of vertical topology (tvert) were then tested for a global clock model (rglobal) using the maximum-likelihood ratio test (Yang 2007).
To estimate divergence times, likelihood ratio test was performed using PAUP*4.0b to obtain the likelihood scores and investigate whether a global clock fit the combined dataset.
Using a maximum-likelihood ratio test, we were able to accept a global clock model for most (75%) of the tvert quartets.
Following the decision that the assumption of a global clock was defensible, divergence times were estimated using r8s [ 58, 59] and BEAST [ 26].
Using PAML (Yang 2007), we generated two models for each protein, one that assumed a global clock across all species and the other that fixed the rate of evolution of each Enallagma protein to a local clock while keeping the rest of the species evolutionary rates confined to a global clock.
