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Evolutionary rates with a strict and a relaxed clock model using a lognormal distribution as prior [75] were obtained with the Bayesian framework implemented in the BEAST program version 1.4, by running 50,000,000 Markov Chain Monte Carlo MCMC with sampling every 5000th generation.
The cost associated with further investigations was modelled using a lognormal distribution.
HZ and PHN utility decrements were tested using a lognormal distribution [ 13].
Seven calibration points were used as priors for divergence times of certain splits, using a lognormal distribution of prior probability.
We calibrated this node using a lognormal prior (mean in real space = 1, log standard deviation = 1.25, offset = 14).
For all datasets, the analyses were run under a GTR + Γ model for each partition, using a lognormal relaxed clock.
Determinants for serological response at baseline were assessed with logistic regression analysis and for individual serotypes using a lognormal model.
To estimate the evolutionary rate we used a lognormal distribution as prior, with a lognormal mean of −6.603 s/s/y and a lognormal stdev of 0.711.
We used a lognormal distribution for fossil calibrations, and a normal distribution for the biogeographic calibrations.
The clock rate was arbitrarily fixed to one, and we used a lognormal distribution as a prior for population size.
To allow uncorrelated rates of evolution across the tree we use a lognormal relaxed clock model, implementing a Yule process as a tree prior.
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