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Box-whisker plots analysis of SDmiRNA pointed highly dispersed values among patients (Figure S3).
However, when central values refer to normal states and dispersed values to diseased states, two (or more) cutoff points are necessary to discriminate these states.
There are many predictive variables whose central values refer to a normal state and whose more dispersed values refer to less preferable states.
The traditional cornerstone of geostatistics has been the exploitation of spatial correlation between dispersed values z u α) to make these predictions at unobserved points using techniques such as kriging (Matheron, 1971).
The latter is necessary when dichotomization results in too much loss of information or when central values refer to normal states and more dispersed values refer to less preferable states, a situation that is not unusual in medical settings (e.g. body temperature, blood pressure).
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Mean values of Enterobacteriaceae showed dispersing values for treated patients and control patients, and this might imply that the enterally added Lactobacillus changes the gut milieu so that the growth of pathogenic bacteria is inhibited.
Initial values of all stochastic nodes of the model were chosen to provide dispersed initial values without being excessively over-dispersed.
Using the normal distribution, this was true only when the proportion of subjects with over dispersed marker values was low and that over dispersion limited.
The MCMC algorithm convergence was assessed by checking the stabilisation of the plots of iterate parameter value, after a given number of samples and by running multiple chains from dispersed starting values.
Convergence of the chains after the initial burn-in was assessed by visual inspection of the time-series plots for the parameter samples as well as Gelman-Rubin diagnostic plots using three sample chains with dispersed starting values [36].
Convergence of the chain after the initial burn-in was assessed by visual inspection of the time-series plots for the parameters as well as Gelman-Rubin diagnostic plots using three sample chains with dispersed starting values [19].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com