Let's say that I am trying to predict the
Sepal Length in
Iris data from
Petal Width, and
Petal Length variables.
Say, we noted that
Petal Length and
Petal Width are grouped as described by the
I am using the following mixed-effects model for this.
libraray(lme4) fit <- lmer(Sepal.Length ~ Sepal.Width + Petal.Length + Petal.Width + (1 + Petal.Length + Petal.Width | Species), data = iris)
My question is how to explain this model concisely in plain language?
For example: In our mixed-effect model, we considered Petal Length and Petal Width to be random effect variables as they may contain variation that can be explained from the Species variable. Further, we assumed all three Sepal Width, Petal Length, and Petal Width are fixed-effect variables.