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Linear Mixed Effects Models

2007
Statistical models provide a framework in which to describe the biological process giving rise to the data of interest. The construction of this model requires balancing adequate representation of the process with simplicity. Experiments involving multiple (correlated) observations per subject do not satisfy the assumption of independence required for ...
Ann L, Oberg, Douglas W, Mahoney
openaire   +2 more sources

Linear Mixed Models II

2001
Observations often fall into groups or clusters. For example, longitudinal data consist of repeated observations on the same subjects. Hierarchical data sets typically consist of subjects nested in higher level units, such as families or GP practices.
Brian Everitt, Sophia Rabe-Hesketh
openaire   +1 more source

Mixed Models

2011
Matthew J. Gurka, Lloyd J. Edwards
openaire   +2 more sources

Nonlinear Mixed Models

2014
Antonio, K., Zhang, Y.
openaire   +2 more sources

Surrogate-Assisted Hybrid-Model Estimation of Distribution Algorithm for Mixed-Variable Hyperparameters Optimization in Convolutional Neural Networks

IEEE Transactions on Neural Networks and Learning Systems, 2023
Jian-Yu Li   +2 more
exaly  

Mixed models.

2017
M. Kaps, W. R. Lamberson
openaire   +1 more source

Mixing Models

2020
Alok Kumar, Mayank Jain
openaire   +1 more source

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