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Distinguished Speaker Series: A Seminar taught by Tyler VanderWeele
“Causal Inference and Outcome-Wide Studies”

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Kristopher Preacher

Kristopher J. Preacher, Ph.D., is Professor in the Quantitative Methods program and Lois Autrey Betts Chair in Education & Human Development at Vanderbilt University. His research concentrates on latent variable models and multilevel analysis, with an emphasis on longitudinal models, mediation, and moderation.

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Particular research areas of interest include exploring the interface between multilevel regression and structural equation modeling, and developing methods for testing mediation and interaction effects in multilevel data. His work has appeared in Psychological Methods, Multivariate Behavioral Research, Behavior Research Methods, Journal of Educational & Behavioral Statistics, Structural Equation Modeling, and the British Journal of Mathematical & Statistical Psychology.

He is an author of Latent Growth Curve Modeling (2008, Sage) and he serves on the editorial boards of Multivariate Behavioral Research, Behavior Research Methods, Journal of Educational & Behavioral Statistics, and Communication Methods & Measures. He is an associate editor of Psychological Methods.

Preacher is the recipient of several prestigious awards including the Sage Publications/Robert McDonald Advancement of Organizational Research Methodology Award (2019), the Distinguished Scientific Award for Early Career Contribution to Psychology (2013) awarded by the American Psychological Association (APA); the Raymond B. Cattell Award for Outstanding Early-Career Contributions to Multivariate Experimental Psychology (2008) awarded by the Society of Multivariate Experimental Psychology; and the Anne Anastasi Early Career Award (2008) awarded by the American Psychological Association Division 5: Evaluation, Measurement, & Statistics. He is a Fellow of both the American Psychological Association and the Association for Psychological Science and was named the Chancellor Faculty Fellow (July, 2015 – June, 2017) at Vanderbilt University.

At Vanderbilt University, he teaches graduate-level courses on Multilevel Modeling, Factor Analysis, Advanced Structural Equation Modeling, Nonparametric Statistics, and Statistical Consulting.

You can visit his personal webpage here.

Google Scholar Citation Page

Dr. Preacher’s books can be found below:

Latent Growth Curve Modeling (Quantitative Applications in the Social Sciences (2008)

Kristopher's Seminars
Livestream

Multilevel Structural Equation Modeling

Weds, May 14 – Fri, May 16,
Mon, May 19 – Weds, May 21, 2025

Hierarchically clustered (multilevel or nested) data are common in the social sciences, medical fields, and business research. Clustered data violate the assumption of independence required by ordinary statistical methods. Increasingly complex research designs and hypotheses have created a need for...

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On-Demand

Exploratory Factor Analysis

Monday, May, 5 —
Monday, June 2, 2025

This seminar covers primarily Exploratory Factor Analysis (EFA), which is used extensively in psychology, education, medicine, and management to identify underlying factors or dimensions that explain the variability in a set of observed variables. EFA can be a powerful tool...

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Livestream

Exploratory Factor Analysis

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This seminar covers primarily Exploratory Factor Analysis (EFA), which is used extensively in psychology, education, medicine, and management to identify underlying factors or dimensions that explain the variability in a set of observed variables. EFA can be a powerful tool...

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On-Demand

Multilevel Modeling: A Second Course

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Hierarchically clustered (multilevel or nested) data are common in the social sciences, medical fields, and business research. Clustered data violate the assumption of independence required by ordinary statistical methods. Increasingly complex research designs and hypotheses have created a need for...

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Livestream

Multilevel Modeling: A Second Course

Ask about upcoming dates

Hierarchically clustered (multilevel or nested) data violate the assumption of independence required by ordinary statistical methods. Increasingly complex research designs and hypotheses have created a need for sophisticated methods that go beyond standard multilevel modeling (MLM). This “second course” in...

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