Hayes, A. F., & Rockwood, N. J. (in press). Regression-based statistical mediation and moderation analysis in clinical research: Observations, recommendations, and implementation. Behaviour Research and Therapy.
Hayes, A. F. & Montoya, A. K. (in press). A tutorial on testing, visualizing, and probing interaction involving a multicategorical variable in linear regression analysis. Communication Methods and Measures
Montoya, A. K., & Hayes, A. F. (in press). Two condition within-participant statistical mediation analysis: A path analytic framework. Psychological Methods
Darlington, R. B., & Hayes, A. F. (2017). Regression analysis and linear models: Concepts, applications, and implementation. New York: The Guilford Press.
Hayes, A. F. (2015). An index of test of linear moderated mediation. Multivariate Behavioral Research, 50, 1-22.
Hayes, A. F., and Preacher, K. J. (2014). Statistical mediation analysis with a multicategorical independent variable. British Journal of Mathematical and Statistical Psychology, 67, 451-470
Hayes, A. F., & Sharkow, M. (2013). The relative trustworthiness of tests of the indirect effect in statistical mediation analysis: Does method really matter? Psychological Science, 24, 1918-1927.
Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression based approach. New York: The Guilford Press [Publishers page]
Hayes, A. F. (2013). Conditional process modeling: Using structural equation modeling to examine contingent causal processes. In G. R. Hancock and R. O. Mueller (Eds.) Structural equation modeling: A second course (2nd Ed). Greenwich, CT: Information Age Publishing.
Hayes, A. F., Glynn, C. J., & Huge, M. E. (2012). Cautions regarding the interpretation of regression coefficients and hypothesis tests in linear models with interactions. Communication Methods and Measures, 6, 1-11.
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.
Hayes, A. F. (2009). Beyond Baron and Kenny: Statistical mediation analysis in the new millennium. Communication Monographs, 76, 408-420.
Hayes, A. F., & Matthes, J. (2009). Computational procedures for probing interactions in OLS and logistic regression: SPSS and SAS implementations. Behavior Research Methods, 41, 924-936.
Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40, 879-891.
Cai, L., & Hayes, A. F. (2008). A new test of linear hypotheses in OLS regression under heteroscedasticity of unknown form. Journal of Educational and Behavioral Statistics, 33, 21-40.
Hayes, A. F., & Cai, L. (2007). Using heteroscedasticity-consistent standard error estimators in OLS regression: An introduction and software implementation. Behavior Research Methods, 39, 709-722.
Hayes, A. F., & Cai, L. (2007). Further evaluating the validity of the conditional decision rule for comparing two independent means. British Journal of Mathematical and Statistical Psychology, 60, 217-244.
Hayes, A. F., & Krippendorff, K. (2007). Answering the call for a standard reliability measure for coding data. Communication Methods and Measures, 1, 77-89.
Preacher, K. J., Rucker, D. D., & Hayes, A. F. (2007). Assessing moderated mediation hypotheses: Theory, methods, and prescriptions. Multivariate Behavioral Research, 42, 185-227.
Hayes, A. F. (2006). A primer on multilevel modeling. Human Communication Research, 32, 385-410.
Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, and Computers, 36, 717-731.
Darlington, R. B., & Hayes, A. F. (2000). Combining independent p-values: Extensions of the Stouffer and binomial methods. Psychological Methods, 5, 496-515.
Hayes, A. F. (2000). Randomization tests and the homoscedasticity assumption when comparing group means. Animal Behaviour, 59, 653-656.
Hayes, A. F. (1998). Within-study meta-analysis: Pooling the significance of doubly-nonindependent ("nonoverlapping") correlations. Psychological Methods, 3, 32-45.
Hayes, A. F. (1997). Cautions in testing variance equality with randomization tests. Journal of Statistical Computation and Simulation, 59, 25-31.
Hayes, A. F. (1996). The permutation test is not distribution-free: Testing H0: rho = 0. Psychological Methods, 1, 184-198.