Sentence examples for mixed modelling techniques from inspiring English sources

Furthermore, we have used mixed modelling techniques to model the progression of disease according to these predictors, allowing a better understanding of the progression over time of this strikingly variable disease.

To remedy this situation, a new system of height-age growth models for P. radiata in New Zealand was developed from a nationwide database using nonlinear mixed modelling techniques.

The optimization process involves both multi-point space mapping, and mixed modeling techniques that utilize space mapping to create a physics-based surrogate model.

Specifically, with the use of trace data about interactions and utilizing the multilevel linear mixed modeling techniques, the study examined whether frequency and duration of student student, student instructor, student system, and student content interactions had an effect of learning outcomes, measured as final course grades.

To test for differences in the variation due to sex and sociality, we made used of mixed modeling techniques to model regression with heteroskedastic residual errors, with maximum likelihood estimation method.

Generally, this confirmed that the nonlinear mixed modelling technique used in the study produced models with good levels of accuracy in estimating height for any given age.

The nonlinear mixed modelling technique used in this study produced models with good levels of accuracy in estimating height for any given age.

A combination of weighted regression, to take into account the unequal selection probabilities of such an inventory design, and mixed model techniques, to accommodate local random fluctuations in the height diameter relationship, were applied to estimate fixed and random parameters for several models reported in the relevant literature.

Such multi-level analyses will use mixed model techniques (hierarchical linear models) [ 35, 36].

The differences between the intervention and control condition over time will be assessed by mixed model techniques to consider factors that may influence the outcomes.

Data with repeated points, such as blood glucose concentrations, will be compared using mixed model techniques, modelling the main effect of treatment group allocation, time and their interaction, with significant main effects and interactions tested using the method of Tukey.