Hand-outs & Summaries

• Statistical Control
• Mediation Analysis
• Reliability and Validity
• General Linear Model I (between)
• Factor Analysis
• Orthogonal Contrasts
• Contrast Analyses
• Dichotomization
• Signal Detection Theory
• Analyses of Reaction Times
• Indicators of Model Fit

Useful links

• How to do a Sobel Test
• Dave Kenny’s web page
• David McKinnon’s web page
• Data Aggregation and Restructuring
• R Scripts for graphing

Useful papers

• Abelson, R. P., & Prentice, D. A. (1997). Contrast Tests of Interaction Hypotheses. Psychological Methods, 2, 315-328.
• Brauer, M. & Curtin, J.J. (2018). Linear mixed-effects models and the analysis of nonindependent data: A unified framework to analyze categorical and continuous independent variables that vary within-subjects and/or within-items. Psychological Methods, 23(3), 389-411.  http://dx.doi.org/10.1037/met0000159
• Brauer, M., & McClelland, G. H. (2005). L’utilisation des contrastes dans l’analyse des données: Comment tester des hypothèses spécifiques dans la recherche en psychologie? [The use of contrasts in data analyses: How should one test specific hypotheses in psychological research? ]. L’Année Psychologique, 105, 273-305.
• Brauer, M. (2002). L’analyse des variables indépendantes continues et catégorielles: Alternatives à la dichotomisation [The analysis of continuous and categorical independent variables: Alternatives to dichotomization]. L’Année Psychologique, 102, 449-484.
• Brauer, M. (2001). Les statistiques et les fours à chaleur tournante: Un outil plutôt qu’une finalité en soi [Statistics and convection ovens: A tool rather than a goal in and of itself]. Les Cahiers Internationaux de Psychologie Sociale, 51-52, 103-108.
• Brauer, M. (2000). L’identification des processus médiateurs dans la recherche en psychologie [The identification of mediating processes in psychological research]. L’Année Psychologique, 100, 661-681.
• Brauer, M., & Judd, C. M. (2000). Defining variables in relationship to other variables: When interactions suddenly turn out to be main effects. Journal of Experimental Social Psychology, 36, 410-423.
• Campbell, M.R., & Brauer, M. (2018). Regression discontinuity analysis.  In B.B.Frey (Ed). The SAGE Encyclopedia of Educational Research, Measurement, and Evaluation (1388-1392). Thousand Oaks, CA: SAGE.
• Garcia-Marques, L., Garcia-Marques, T., & Brauer, M. (2014). Buy three but get only two: The smallest effect in a 2 × 2 ANOVA is always uninterpretable. Psychonomic Bulletin & Review, 21(6), 1415-1430.
• Judd, C. M., Kenny, D. A., McClelland, G. H. (2001). Estimating and testing mediation and moderation in within-subject designs. Psychological Methods, 6, 115-134.
• Kline, R. B. (2015). Positive Definiteness. Principles and practice of structural equation modeling. Guilford publications, 49-53.
• MacCallum, R. C., Zhang, S., Preacher, K. J., Rucker, D. D. (2002). On the practice of dichotomization of quantitative variables. Psychological Methods, 7, 19-40.
• Muller, D., Judd, C. M., & Yzerbyt, V. Y. (2005). When moderation is mediated and mediation is moderated. Journal of Personality and Social Psychology, 89, 852-863.
• Murrar, S. & Brauer, M. (2018). Mixed-model analysis of variance. In B.B. Frey (Ed). The SAGE Encyclopedia of Educational Research, Measurement, and Evaluation (1075-1078). Thousand Oaks, CA: SAGE.
• Musca, S. C., Kamiejski, R., Nugier, A., Méot, A., Er-rafiy, A., & Brauer, M. (2011). Data with hierarchical structure: Impact of intraclass correlation and sample size on Type-I error. Frontiers in Quantitative Psychology and Measurement, 2, Art. 74, 1-6.
• Petty, R. E., Fabrigar, L. R., Wegener, D. T., Priester, J. R. (1996). Understanding data when interactions are present or hypothesized. Psychological Science, 7, 247-252.