title: [Interaction in ANOVA: misconceptions].
abstract: Although interaction in analysis of variance has an unequivocal theoretical meaning (and so it appears in the statistic literature), frequent misconceptions are found in empirical research, which, in many cases, lead to wrong conclusions. In this paper, 150 articles are reviewed: in 12.7% of them, no attention is paid to the interaction (either because it is not analysed or because it is analysed but not discussed); in 79.1%, interaction is studied through simple effects analysis; and only in 8.2% of the cases, interaction is correctly discussed. It could be that psychology researchers tend to analyse and interpret the interaction between factors incorrectly because the most widespread statistic packages (with SPSS in the lead) do not allow performing the comparisons needed to analyse a significant interaction in factorial designs with randomized groups. In order to contribute to eradicating this problem, we herein show how to design some of the linear comparisons that allow isolating the interaction effect, and we explain how to use SPSS to compute these comparisons.
authors.affiliation: Universidad Autónoma de Madrid. antonio.pardo@uam.es
authors.forename: Antonio
authors.initials: A
authors.lastname: Pardo
authors.forename: Jesús
authors.initials: J
authors.lastname: Garrido
authors.forename: Miguel A
authors.initials: MA
authors.lastname: Ruiz
authors.forename: Rafael
authors.initials: R
authors.lastname: San Martín
mesh_terms: D000704:Analysis of Variance; D003627:Data Interpretation, Statistical; D006801:Humans; D008960:Models, Psychological; D011584:Psychology / Q000379:methods* / Q000706:statistics & numerical data*