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Journal Article 1: May, K., & Hittner, J. B. (2012). Effect of correlation on power in within-subjects versus between-subjects designs. Comprehensive Psychology,1.

Abstract: It is well known that the two dependent-samples t test (and a within-subjects design in general) is typically more powerful than the two independent samples t test (a between-subjects design), and that this increase in power is in large part a function of the correlation between the two sets of scores (e.g., pre-test and post-test). This paper demonstrates relative power as a function of (1) the correlation between groups with effect size and sample size held constant and (2) sample size with the correlation between groups and effect size held constant.

Journal Article 2: Dong, N. (0014). Using propensity score methods to approximate factorial experimental designs to analyze the relationship between two variables and an outcome. American Journal of Evaluation, 36, 42–66.

Abstract: Researchers have become increasingly interested in programs’ main and interaction effects of two variables (A and B, e.g., two treatment variables or one treatment variable and one moderator) on outcomes. A challenge for estimating main and interaction effects is to eliminate selection bias across A-by-B groups. I introduce Rubin’s causal model to approximate factorial experimental designs for studies with partial randomization and nonrandomization. I apply a Monte Carlo simulation to evaluate several propensity score applications. The findings suggest the following two applications for reducing bias and mean square error of parameter estimates when analyzing the relationship of two variables and an outcome: (a) inverse of propensity score weighting based on one multinomial propensity score model and (b) subclassification based on two binary propensity score models. As a demonstration, I examine whether the effects of the Head Start program, compared to other center-based care, for improving children’s reading achievement vary by child care quality.

Journal Article 3: Stansbury, J. A., & Munro, G. D. (2013). Gaming in the classroom: An innovative way to teach factorial designs. Teaching of Psychology, 40, 148–152.

Abstract: This study tested the effectiveness of video game use for instruction of factorial designs in a research methods course. Students designed and conducted a mini study, playing "Dance, Dance, Revolution", using video game scores as the dependent variable. A mixed-design analysis of variance revealed a significantly greater increase from pretest to posttest in content knowledge in the Wii activity condition compared to lecture-only and no-content control conditions. Implementing this nontraditional teaching method engaged students and increased knowledge of factorial designs in a research method course.