From Wikipedia:

a mixed-design analysis of variance model (also known as a split-plot ANOVA) is used to test for differences between two or more independent groups whilst subjecting participants to repeated measures. Thus, in a mixed-design ANOVA model, one factor (a fixed effects factor) is a between-subjects variable and the other (a random effects factor) is a within-subjects variable. Thus, overall, the model is a type of mixed effect model.

My questions:

  1. What relation is between mixed design and split-plot design? Is a split-plot design a within-subject design, or a between-subject design, or both?
  2. Why is the model of a mixed design a mixed effect model? Which input variable has random effect and which input variable has fixed effect?

1 Answer 1


I'm sure terminology varies, but I think it's fair to say that a split-plot design (where there are two or more treatments imposed at different hierarchical levels) is a specific example of a mixed design. Mixed effect models (also called multilevel or hierarchical models; repeated measures are another special case) are so-called because they include both random and fixed effect terms.

I would say that split-plot designs are "both" between- and within-subject designs, because (at least) one treatment is between- and (at least) one treatment is within-subject.

In order to answer the other question one would need a more specific example.

  • $\begingroup$ +1 but I think one can answer Q2 as well: both between- and within- factors are treated as fixed, whereas the plot id (aka subject id) is a grouping variable that is treated as random. $\endgroup$
    – amoeba
    Commented May 13, 2019 at 15:23

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Not the answer you're looking for? Browse other questions tagged or ask your own question.