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This is the R code I used for my model:

M4 <- lmer(Average ~ Region + (1|Participant),data=Theta)

tab_model(M4,show.se=T,digits = 4,
          title="Table: Model for the Relationship of Average Power in the Theta Frequency with 

the four Brain Regions")

summary(M4)

In Region there are four predictors: Central, Frontal, Occipital and Posterior. The output, however, only shows Frontal, Occipital and Posterior.

Average

Predictors  Estimates   std. Error  CI  p

(Intercept) 0.3473  0.0390  0.2709 – 0.4238 <0.001

Region [Frontal]    0.0938  0.0087  0.0767 – 0.1109 <0.001

Region [Occipital]  -0.1437 0.0087  -0.1608 – -0.1267   <0.001

Region [Posterior]  -0.0069 0.0087  -0.0239 – 0.0102    0.430

Why is that and is this something that can be fixed?

Dove
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  • Central is the referent – jpsmith Aug 30 '22 at 23:38
  • See the linked question and answer. When you have categorical predictors, the first (alphabetically or by factor level) is used as the reference level to which others are compared, so does not have its own coefficient. – neilfws Aug 30 '22 at 23:41

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