main effect

Terms from Statistics for HCI: Making Sense of Quantitative Data

In an ANOVA the main effect is the measured effect of one of the conditions averaging out the contribution of all other factors. This is in contrast to the interaction effect between conditions.
For example, suppose we have measured the following error rates (averaged over many replications, and assuming equal numbers of replication in each cell):
system A system B
novice 70 50
expert 10 30
The main effect of expertise is that novices have (on average) 40 more errors than experts. The main effect of the system is zero as the decrease in performance for experts precisely matches the improvement for novices.

Used in Chap. 14: page 171

Also used in hcistats2e: Chap. 12: page 138

Used in glossary entries: ANOVA (Analysis of Variance), interaction effect