#### Contact Information

Email

Lab Website

615-343-1648

202A Hobbs

#### Research Area

#### Education

Postdoc, The University of of North Carolina at Chapel Hill, 2006

Ph.D., The Ohio State University, 2003

M.A., The College of William & Mary, 1998

#### Curriculum Vitae

#### Current Courses

Introduction to Statistical Analysis (Undergraduate; PSY-PC 2101)

Multilevel Modeling (Graduate; PSY-GS 321)

#### Advising

#### Societies

American Psychological Association (APA, Division 5)

Association for Psychological Science (APS)

Psychometric Society

Society for Personality and Social Psychology (SPSP)

Society of Multivariate Experimental Psychology (SMEP)

# Kristopher J. Preacher

### Associate Professor

Dr. Preacher is Associate 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*, *Multivariate Behavioral Research*, and *Communication Methods and Measures*.

#### Representative Publications

Preacher, K. J. (in press). Advances in mediation analysis: A survey and synthesis of new developments. *Annual Review of Psychology*.

Lachowicz, M. J., Sterba, S. K., & Preacher, K. J. (in press). Investigating multilevel mediation with fully or partially nested data. *Group Processes & Intergroup Relations*.

Wang, L., & Preacher, K. J. (in press). Moderated mediation analysis using Bayesian methods. *Structural* *Equation Modeling*.

Hayes, A. F., & Preacher, K. J. (in press). Statistical mediation analysis with a multicategorical independent variable. *British Journal of Mathematical & Statistical Psychology*.

Pornprasertmanit, S., Lee, J., & Preacher, K. J. (in press). Ignoring clustering in confirmatory factor analysis: Some consequences for model fit and standardized parameter estimates. *Multivariate **Behavioral Research*.

Gu, F., Preacher, K. J., Wu, W., & Yung, Y.-F. (2014). A computationally efficient state space approach to estimating multilevel regression models and multilevel confirmatory factor models. *Multivariate **Behavioral Research*, *49*, 119-129.

Gu, F., Preacher, K. J., & Ferrer, E. (2014). A state space modeling approach to mediation analysis. *Journal of Educational and Behavioral Statistics*, *39*, 117-143.

Sterba, S. K., Preacher, K. J., Forehand, R., Hardcastle, E. J., Cole, D. A., & Compas, B. E. (2014). Structural equation modeling approaches for analyzing partially nested data. *Multivariate Behavioral Research*, *49*, 93-118.

Cole, D. A., & Preacher, K. J. (2014). Manifest variable path analysis: Potentially serious and misleading consequences due to uncorrected measurement error. *Psychological Methods*, *19*, 300-315.

Geldhof, G. J.*, Preacher, K. J., & Zyphur, M. J. (2014). Reliability estimation in a multilevel confirmatory factor analysis framework. *Psychological Methods*, 19, 72-91.

Cho, S.-J., Athay, M.*, & Preacher, K. J. (2013). Measuring change for a multidimensional test using a generalized explanatory longitudinal item response model. *British Journal of Mathematical & Statistical Psychology*, *66*, 353-381.

Preacher, K. J., Zhang, G., Kim, C., & Mels, G. (2013). Choosing the optimal number of factors in exploratory factor analysis: A model selection perspective. *Multivariate Behavioral Research*, *48*, 28-56.

Zhang, G., Preacher, K. J., & Jennrich, R. I. (2012). The infinitesimal jackknife with exploratory factor analysis. *Psychometrika*, *77*, 634-648.

Selig, J. P.*, Preacher, K. J., & Little, T. D. (2012). Modeling time-dependent association in longitudinal data: A lag as moderator approach. *Multivariate Behavioral Research*, *47*, 697-716.

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.

* Current or former Quantitative student.