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The model chosen has distinct advantage of associating the transition model with experimental data [21, 22, 23, 24].
It is shown that the sensitivity of the γ-˜Reθt transition model with respect to shape variations allows its use in a design framework.
Due to a lack of epidemiological data, we estimated the population at risk (distinguishing between normal, moderate and high risk of pneumococcal disease) in 83 age groups (18 100 years of age) in the above mentioned setting as well as the proportion of immunized individuals due to vaccination in each age/risk group using a Markov state transition model with a time horizon of 100 years.
We then estimated a latent transition model with five classes.
We proceeded to fit the latent transition model with three classes.
To further distinguish between these two transition approaches, we have derived a merged transition model with modified transition probabilities q ′.
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This model is reported to have a distinct advantage of associating transition modelling with experimental data [21, 22, 23, 24].
122, 273 284] and Lodefier et al. [Lodefier, K., Merci, B., De Langhe, C., Dick, E., 2003. Transition modelling with the SST turbulence model and intermittency transport equation.
Or, one could fit several different transition models with different modelling selections and draw inferences for interested transition probabilities from corresponding models.
Results: We present a highly parallelizable local enumeration scheme that enables the computation of exact macro-state transition models with highly reduced memory requirements.
We constructed an individual Markov state-transition model with weekly cycles with TreeAge Pro 2013 software (Williamstown, MA, USA).
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