Analytic variance expressions are provided that include sampling variability and model variability in situations where multiple models are employed to generate estimates of biomass.
However, our goal here is to evaluate the effects of information we can gather from sequence data alone and to model variability in expression levels and breadths separately.
Incorporation of these covariates in the final model explained approximately 24%and52%2% of the base model variability of CL and Vc, respectively.
The AIC approach computes goodness-of-fit (accuracy) and model variability (precision) to quantitatively rank different models in order to select the most parsimonious model (Saffron et al. 2006).
The direct temperature response of NEE contributed between 30 37% of model variability in the Northern Hemisphere and 39 40% in the Southern Hemisphere.
A recent review [ 6], highlighting a number of important features which have yet to be explored in paratuberculosis modelling research emphasised treatment of parameter uncertainty and model variability as key areas for improvement.
Owing to the hierarchical structure of the data and the planned missingness design, analyses will be performed within the linear mixed models framework, such as to model the variability and dependency at the different levels.
To account for this structure and to model variability at each level, we used mixed effects models with the xtmixed command in Stata.
