Fixed effects

Fixed effects are

• the model’s intercept and slopes.
• a new name for the \(\beta\) coefficients that you’re already familiar with from DAPR2.
• the estimated average intercept/slope values for the whole dataset, averaging over levels of the grouping variable(s).

In the example lmer() structure below, the fixed effects appear in the 1 + x1 + x2 + ... bit:

The term “fixed effect” is used to distinguish these parameters from “random effects”.

Linked flash cards

Outgoing links

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Backlinks

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