Contact Information
Email
Lab Website
615-343-1648
202A Hobbs
Research Area
Education
Ph.D., Ohio State University, 2003
M.A., The College of William & Mary, 1998
Curriculum Vitae
Current Courses
Intro. to Statistical Analysis (Undergraduate; PSYC 2101)
Hierarchical Linear Modeling (Graduate; PSY-GS 319 / SPED 3016)
Kristopher J. Preacher
Assistant Professor
Dr. Preacher is Assistant Professor in the Quantitative Methods program. His research concerns the use (and combination) of structural equation modeling and multilevel modeling to model correlational and longitudinal data. Other interests include developing techniques to test mediation and moderation hypotheses, bridging the gap between substantive theory and statistical practice, and studying model evaluation and model selection in the application of multivariate methods to social science questions. He serves on the editorial boards of Psychological Methods, Journal of Counseling Psychology, Communication Methods and Measures, and Multivariate Behavioral Research.
Representative Publications
Preacher, K. J., Zhang, G., Kim, C., & Mels, G. (in press). Choosing the optimal number of factors in exploratory factor analysis: A model selection perspective. Multivariate Behavioral Research.
Cho, S.-J., Athay, M., & Preacher, K. J. (in press). Measuring change for a multidimensional test using a generalized explanatory longitudinal item response model. British Journal of Mathematical & Statistical Psychology.
Selig, J. P., Preacher, K. J., & Little, T. D. (in press). Modeling time-dependent association in longitudinal data: A lag as moderator approach. Multivariate Behavioral Research.
Zhang, G., Preacher, K. J., & Jennrich, R. I. (in press). The infinitesimal jackknife with exploratory factor analysis. Psychometrika.
Preacher, K. J., & Selig, J. P. (2012). Advantages of Monte Carlo confidence intervals for indirect effects. Communication Methods & Measures, 6, 77-98.
Kelley, K., & Preacher, K. J. (2012). On effect size. Psychological Methods, 17, 137-152.
Preacher, K. J., & Merkle, E. C. (2012). The problem of model selection uncertainty in structural equation modeling. Psychological Methods, 17, 1-14.
Preacher, K. J. (2011). Multilevel SEM strategies for evaluating mediation in three-level data. Multivariate Behavioral Research, 46, 691-731.
Preacher, K. J., & Kelley, K. (2011). Effect size measures for mediation models: Quantitative strategies for communicating indirect effects. Psychological Methods, 16, 93-115.
Preacher, K. J., Zhang, Z., & Zyphur, M. J. (2011). Alternative methods for assessing mediation in multilevel data: The advantages of multilevel SEM. Structural Equation Modeling, 18, 161-182.
Preacher, K. J., Zyphur, M. J., & Zhang, Z. (2010). A general multilevel SEM framework for assessing multilevel mediation. Psychological Methods, 15, 209-233.
Hayes, A. F., & Preacher, K. J. (2010). Quantifying and testing indirect effects in simple mediation models when the constituent paths are nonlinear. Multivariate Behavioral Research, 45, 627-660.
Zhang, G., Preacher, K. J., & Luo, S. (2010). Bootstrap confidence intervals for ordinary least squares factor loadings and correlations in exploratory factor analysis. Multivariate Behavioral Research, 45, 104-134.
Zhang, Z., Zyphur, M. J., & Preacher, K. J. (2009). Testing multilevel mediation using hierarchical linear models: Problems and solutions. Organizational Research Methods, 12, 695-719.