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Data and models

In the following, all demos of Monolix are presented. They were build to explore all functionalities of Monolix in terms of model creations, continuous and non continuous outcomes management, joint models for multivariate outcomes, models for the individual parameters, pharmacokinetic models, and some extensions.

Defining a data set

Creating and using models

  • Libraries of models: learn how to use the Monolix libraries of PKPD models and create your own libraries.
  • Use your own model: learn how to use your own libraries created from scratch or from the libraries.
  • Outputs and Tables: learn how to define outputs and create tables with selected outputs of the model.
  • Residual error model: learn how to use the predefined residual error models.
  • Handling censored data: learn how to handle easily and properly censored data, i.e. data below (resp. above) a lower (resp.upper) limit of quantification (LOQ) or detection (LOD).
  • Mixture of structural models: learn how to implement between subject mixture models (BSMM) and within subject mixture models (WSMM).
  • Time-to-event data model: learn how to implement a model for (repeated) time-to-event data.
  • Count data model: learn how to implement a model for count data, including hidden Markov model.
  • Categorical data model: learn how to implement a model for categorical data, assuming either independence or a Markovian dependence between observations.