When I get 2 mixed linear Models for a comparison between them
For example, (B, C, D are factors)
Mdoel 1 <- lmer(A ~ B * C * D + (1|individual), data = Data_1) in script Outcome in console: A ~ B * C * D + (1 | individual)
Model 2 <- update(Model 1, . ~ . - B : C : D) in script Outcome in console : A ~ B + C + D + (1 | individual) + B:C + B:D + C:D
- Also, B,C,D are for fixed effects and (1|individual) is for a random effect
What is the difference between A ~ B + C + D + (1|individual) and A ~ BCD + (1|individual)?
- By Model 2 what do mean ". ~ ." and "- B : C : D" both in Script?
2-2. A ~ B + C + D + (1 | individual) + B:C + B:D + C:D What does mean " B:C + B:D + C:D "?