8:00 am - 5:00 pm MDT
This training is designed for modelers who already have some experience with Monolix,, who wish to i) better understand the algorithms and their options, ii) learn how to implement complex models, iii) improve their strategy for model building.
The course will alternate lectures and interactive hands-on sessions with Monolix.
I – Algorithms and good practices for parameter estimation
- Estimating the population parameters: theory and practice
- SAEM and its settings
- Assessing the convergence
- Handling parameters without variability
- Bayesian estimation of population parameters
- Settings of MCMC: transition kernels, automatic stopping rule
- Estimating the Fisher Information Matrix with linearization or stochastic approximation
- Estimating the likelihood with linearization or importance sampling Monte Carlo
II – Methods for statistical model building
- Diagnostics for the statistical model
- Interpretation of diagnostic plots
- Performing unbiased statistical tests
- Defining and using the shrinkage correctly
- Strategies for automatic model building
- Covariate search using COSSAC
- Model building using SAMBA
III – Implementing complex PKPD models
- Modeling non-continuous data
- Sequential and simultaneous approaches for joint models
- Complex statistical models
- Non-standard inter-individual variability
- Inter-occasion variability
- Complex covariate-parameter relationships
To register for these workshops use the ACoP13 registration form.
If you have any questions or difficulty registering for the workshop, please send an email directly to email@example.com.