- Between-subjects evaluates (a) whether at least two of the levels of each factor represent populations with different mean values; and (b) whether there is a significant interaction between the n factors (i.e., it evaluates the variation among the differences between means for different levels of each factor over different levels of the other factor).
- The data can be balanced or unbalanced (unequal group sizes).
- The method allows using:
- Fixed-effects model: Any number of factors can be used with fixed-effects model (1, 2, 3, ..., n-way)
- Random-effects model: Not more than two factors can be used with random-effects model.
- Mixed-effects model: Can use two factors, one to be treated as random and one as fixed.

The analysis output including the default and optional ones can include:

- Multifactor cell means table
- Between-subjects ANOVA table
- Measures of association (variance-accounted for statistics)
- Effect size measures in standardized units of mean difference
- Regression coefficients and model summary output
- Normality test on regression residuals of total model:
- D'Agostino-Pearson test
- Shapiro-Wilk test

- Homoscedasticity tests on regression residuals of total model (Bartlett, Levene, and Brown-Forsythe)

- Pairwise multiple comparisons (PMC) accompanying the between-subjects ANOVA module:
- Bonferroni-Dunn
- Dunn-Sidak
- Dunnett
- Scheffé
- Tukey-Kramer
- Fisher's LSD

- Tukey's HSD
- Newman-Keul
- Tukey B
- Dunnett's C
- Games-Howell

The tables on this page are examples from a three-way design whose factors and cell means are shown below:

Depending on the selected test(s) and analysis options, the PMC output can include:

- PMC pooled over all factors
- PMC at fixed levels of one other factor (this option requires running two-way or higher dimensions ANOVA)
- PMC at fixed levels of two other factors (this option requires running three-way or higher dimensions ANOVA) (see the example below).

- This option provides a PMC table for each factor with
*k*>=3 levels. In the example shown here, the ANOVA test results indicate:- The main effects of Factor A and Factor B (each havng
*k*=2 levels) are significant, and the main effect of Factor C is insignificant. However, as shown below, the PMC at fixed levels of two other factors reveal differences that were otherwise masked.

- The main effects of Factor A and Factor B (each havng

- In the current example, this option provides three PMC tables as follows:

- In the current example, this option provides Two PMC tables as follows: