Mixed-Effects Model

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A Mixed-Effects Model is a statistical model that is a fixed effects model and a random effects model.



References

2015

2014

  • https://www.mathworks.com/help/stats/linear-mixed-effects-models.html
    • QUOTE: Linear mixed-effects models are extensions of linear regression models for data that are collected and summarized in groups. These models describe the relationship between a response variable and independent variables, with coefficients that can vary with respect to one or more grouping variables. A mixed-effects model consists of two parts, fixed effects and random effects. Fixed-effects terms are usually the conventional linear regression part, and the random effects are associated with individual experimental units drawn at random from a population. The random effects have prior distributions whereas fixed effects do not. Mixed-effects models can represent the covariance structure related to the grouping of data by associating the common random effects to observations that have the same level of a grouping variable.