The article introduces a new method called latent repeated measures analysis of variance (L-RM-ANOVA) to analyze data from experiments. Unlike traditional methods, L-RM-ANOVA not only looks at average effects but also considers individual differences in how factors affect outcomes. This approach uses structural equation modeling to examine complex contrasts and can handle multi-factorial designs. The researchers demonstrate L-RM-ANOVA with a practical example to show its effectiveness in understanding interindividual differences in experimental results.