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;Linearity
[[File:Linearity Graphs.jpg|thumb|289x289px]]
The assumption of linearity states that there is a rectilinear (straight-line, as opposed to non-linear or U-shaped) relationship between variables.<ref name="Green" /> However, the model can be extended to nonlinear relationships.<ref>{{cite journal |title=Nonlinear Multilevel Models, with an Application to Discrete Response Data |first=Harvey |last=Goldstein |journal=Biometrika |volume=78 |issue=1 |year=1991 |pages=45–51 |jstor=2336894 |doi=10.1093/biomet/78.1.45}}</ref> Particularly, when the mean part of the level 1 regression equation is replaced with a non-linear parametric function, then such a model framework is widely called the [[nonlinear mixed-effects model]].<ref name="ReferenceA"/>
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