Main effect
Topic of Analysis of variance examples, part of Data analysis
Main effect
| Type | Topic |
| Taught in | Analysis of variance examples |
| Part | Data analysis |
In a factorial design, the effect of one factor averaged over the levels of the others. When the factors interact, a main effect alone can mislead, because the effect of one factor then depends on the level of the other.
In Analysis of variance examples
Here \mu is a baseline mean, \alpha_i and \beta_j are the main effects of the two factors, and \gamma_{ij} is their interaction. The parameters are not all identifiable as written; R fixes them by setting the effects of the first level of each factor to zero.
Used in
See also
Bonferroni correction · Interaction · Checking an analysis-of-variance model · Which groups differ? · Two-factor analysis of variance · Randomisation and blocking