Degree course change and student performance: a mixed-effect model approach

2015 ◽  
Vol 43 (1) ◽  
pp. 3-15 ◽  
Author(s):  
Giada Adelfio ◽  
Giovanni Boscaino
Keyword(s):  
Student Performance ◽  
Mixed Effect Model ◽  
Mixed Effect ◽  
Effect Model ◽  
Model Approach

A mixed effect model approach for assessing land‐based mitigation in Integrated Assessment Models: a regional perspective

2021 ◽  
Author(s):  
Thais Diniz Oliveira ◽  
Thierry Brunelle ◽  
Bertrand Guenet ◽  
Philippe Ciais ◽  
Florian Leblanc ◽  
...  
Keyword(s):  
Integrated Assessment ◽  
Mixed Effect Model ◽  
Mixed Effect ◽  
Integrated Assessment Models ◽  
Effect Model ◽  
Model Approach ◽  
Regional Perspective

scholarly journals Pemodelan Farmakokinetika Berbasis Populasi dengan R: Model Dua Kompartemen Ekstravaskuler

2018 ◽  
Vol 4 (1) ◽  
pp. 26-35
Author(s):  
Dion Notario
Keyword(s):  
Differential Equations ◽  
Predictive Model ◽  
Goodness Of Fit ◽  
Population Based ◽  
Linear Mixed Effect Model ◽  
Mixed Effect Model ◽  
Mixed Effect ◽  
Effect Model ◽  
Residual Plot ◽  
Model Approach

A Tutorial of two-compartment extravascular population-based pharmacokinetics modeling was performed by differential equations and non-linear mixed effect model approach. First, three-level differential equations of two-compartment pharmacokinetics were generated. Then, covariate and non-covariate models were developed by nlmeODE and nlme packages installed in R. The best model was selected according to AIC, BIC, and LogLik value. A model without covariates model was selected as the best model. The selected model showed a goodness of fit with experimental dataset and residual plot of the model revealed that no violations of model assumtions.  In conclusion, nlme and nlmeODE is capable to generate an adequate predictive model of two-compartment population-based pharmacokinetics for extravascular route

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