Mixed Designs Lecture Vocabulary

These flashcards cover the key terminology and concepts related to mixed research designs, including factor identification, types of analyses, and specific statistical models.

Mixed Designs

Designs that incorporate both between- and within-subjects factors or designs, typically factorial in nature.

Between-subjects Factors

Factors involving differences between people or groups of people.

Within-subjects Factors

Factors involving differences within people at different points in time.

Affective Forecasting

How well someone's anticipated feelings match their actual feelings, or how good people are at predicting their future affect.

Mixed Models

Statistical analyses that can model and account for both dependent and independent data.

Mixed-design ANOVA

An ANOVA that assesses main effects of between- and within-subjects factors, along with their interactions, assuming the dependent variable is interval/ratio.

Generalized Linear Mixed Models

Regression analyses that can test both independent and dependent data, used when at least one factor is measured at the interval/ratio level.

Adjusted Score Approaches

Methods involving taking scores from one condition in the within-subject factor and adjusting them, such as calculating a "difference score" (e.g., time 2 score – time 1 score) or "covarying out" one score from another.