neue Veröffentlichung: On the Relationship between ANOVA Main Effects and Average Treatment Effects

Gemeinsam mit ihren Kolleg*innen Linda Gräfe von der Universität Jena und Prof. Dr. Axel Mayer von der Universität Bielefeld hat Dr. Sonja Hahn einen neuen Beitrag zur quantitativen Forschungsmethodik in der internationalen Fachzeitschrift Multivariate Behavioral Research veröffentlicht:

On the Relationship between ANOVA Main Effects and Average Treatment Effects

We adopt a causal inference perspective to shed light into which ANOVA type of sums of squares (SS) should be used for testing main effects and whether main effects should be considered at all in the presence of interactions. We consider balanced, proportional and nonorthogonal designs, and models with and without interactions. When the design is balanced, we show that the average treatment effect is estimated by the main effects obtained by type I, II, and III sums of squares. In proportional designs, we show that the average treatment effect is estimated by the the type I and type II main effects, whereas type III SS yield biased estimates of the average treatment effect if there are interactions. When the design is nonorthogonal, ANOVA type I is always highly biased and ANOVA type II and III main effects are biased if there are interactions. We include a simulation study to illustrate the magnitude of the bias in estimating the average treatment effect across a variety of conditions, and provide recommendations for applied researchers. [Abstract]

Link zur Veröffentlichung: https://www.tandfonline.com/doi/full/10.1080/00273171.2022.2068122

Die App, die hier zum Veranschaulichen der unterschiedlichen Effekte genutzt wurde, kann hier ausprobiert werden.