Results 271 to 280 of about 1,828,929 (311)
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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

Antibody–drug conjugates: Smart chemotherapy delivery across tumor histologies

Ca-A Cancer Journal for Clinicians, 2022
Paolo Tarantino   +2 more
exaly  

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

An overview of real‐world data sources for oncology and considerations for research

Ca-A Cancer Journal for Clinicians, 2022
Lynne Penberthy   +2 more
exaly  

Mixed models.

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

The biofilm life cycle: expanding the conceptual model of biofilm formation

Nature Reviews Microbiology, 2022
Karin Sauer   +2 more
exaly  

Mixing Models

2020
Alok Kumar, Mayank Jain
openaire   +1 more source

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