Compas, B. E., Bemis, H., Gerhardt, C. A., Dunn, M. J., Rodriguez, E. M., Desjardins, L., Preacher, K. J., Manring, S., & Vannatta, K. (in press). Mothers and fathers coping with their children's cancer: Individual and interpersonal processes. Health Psychology.
Preacher, K. J., Zhang, Z., & Zyphur, M. J. (in press). Multilevel structural equation models for assessing moderation within and across levels of analysis. Psychological Methods.
Rucker, D. D., McShane, B. B., & Preacher, K. J. (in press). A researcher's guide to regression, discretization, and median splits of continuous variables. Journal of Consumer Psychology.
Cho, S.-J., Preacher, K. J., & Bottge, B. A. (in press). Detecting intervention effects in a cluster randomized design using multilevel structural equation modeling for binary responses. Applied Psychological Measurement.
Merkle, E. C., You, D., & Preacher, K. J. (in press). Testing non-nested structural equation models. Psychological Methods.
Deboeck, P. R., & Preacher, K. J. (in press). No need to be discrete: A method for continuous time mediation analysis. Structural Equation Modeling.
Lachowicz, M. J.*, Sterba, S. K., & Preacher, K. J. (2015). Investigating multilevel mediation with fully or partially nested data. Group Processes & Intergroup Relations, 18, 274-289.
Preacher, K. J. (2015). Advances in mediation analysis: A survey and synthesis of new developments. Annual Review of Psychology, 66, 825-852.
Laird, K. T., Preacher, K. J., & Walker, L. S. (2015). Attachment and adjustment in adolescents and young adults with a history of pediatric functional abdominal pain. The Clinical Journal of Pain, 31, 152-158.
Richter, K. P., Shireman, T. I., Ellerbeck, E. F., Cupertino, A. P., Cox, L. S., Preacher, K. J., Spaulding, R., Mussulman, L. M., Nazir, N., Hunt, J. J., & Lambart, L. (2015). Comparative and cost effectiveness of telemedicine versus telephone counseling for smoking cessation. Journal of Medical Internet Research, 17, e113.
Wang, L., & Preacher, K. J. (2015). Moderated mediation analysis using Bayesian methods. Structural Equation Modeling., 22, 249-263.
Preacher, K. J., & Hancock, G. R. (2015). Meaningful aspects of change as novel random coefficients: A general method for reparameterizing longitudinal models. Psychological Methods, 20, 84-101.
Timmons, A. C.*, & Preacher, K. J. (2015). The importance of temporal design: How do measurement intervals affect the accuracy and efficiency of parameter estimates in longitudinal research? Multivariate Behavioral Research, 50, 41-55.
Pornprasertmanit, S., Lee, J., & Preacher, K. J. (2014). Ignoring clustering in confirmatory factor analysis: Some consequences for model fit and standardized parameter estimates. Multivariate Behavioral Research, 49, 518-543.
Hayes, A. F., & Preacher, K. J. (2014). Statistical mediation analysis with a multicategorical independent variable. British Journal of Mathematical & Statistical Psychology, 67, 451-470.
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.
* Current or former Quantitative student.