In his research, he is interested in developing new methods for modeling change in (intensive) longitudinal data and for investigating if, how, and for whom an intervention, such as a psychotherapeutic treatment or a health training, has an effect. His methodological research emphasis is on development and application of models for analyzing average and conditional (causal) effects, causal mediation models, latent state-trait models (for experience sampling data) and models for latent change. Substantive research focuses include quality of life research (e.g. on fatigue in students and cancer patients) and research on learning and development processes across the lifespan. An important aspect of his research is the development of user-friendly statistical software, to make modern statistical methods and models available for a broader audience.
• Mayer, A., Zimmermann, J., Hoyer, J., Salzer, S., Wiltink, J., Leibing, E., & Leichsenring, F. (2020). Interindividual differences in treatment effects based on structural equation models with latent variables: An EffectLiteR tutorial. Structural Equation Modeling, 27, 798-816. https://doi.org/10.1080/10705511.2019.1671196
• Stadtbäumer, N., Müller, H., Goergen, H., Kreissl, S., Borchmann, P., & Mayer, A. (2020). The interplay between cancer-related fatigue and functional health in Hodgkin lymphoma survivors. Health Psychology, 39, 905-911. https://doi.org/10.1037/hea0000921
• Langenberg, B., Helm, J. L., & Mayer, A. (2020). Repeated measures ANOVA with latent variables to analyze interindividual differences in contrasts. Multivariate Behavioral Research, 1-19. https://doi:10.1080/00273171.2020.1803038
• Flunger, B., Mayer, A., & Umbach, N. (2019). Beneficial for some or for everyone? Exploring the effects of an autonomy-supportive intervention in the real-life classroom. Journal of Educational Psychology, 111, 210–234. https://doi.org/10.1037/edu0000284
• Mayer, A. (2019). Causal inference based on latent variable models. Methodology, 15, 15–28, https://doi.org/10.1027/1614-2241/a000174
• Mayer, A. & Thoemmes, F. (2019). Analysis of variance models with stochastic group weights. Multivariate Behavioral Research, 54, 542-554, https://doi.org/10.1080/00273171.2018.1548960
• Kiefer, C., & Mayer, A. (2019). Average effects based on regressions with a logarithmic link function: A new approach with stochastic covariates. Psychometrika, 84, 422-446. https://doi.org/10.1007/s11336-018-09654-1
• Mayer, A., Umbach, N., Flunger, B. & Kelava, A. (2017). Effect analysis using nonlinear structural equation mixture modeling. Structural Equation Modeling, 24, 556-570, https://doi.org/10.1080/10705511.2016.1273780
• Mayer, A., Dietzfelbinger, L., Rosseel, Y. & Steyer, R (2016) The EffectLiteR approach for analyzing average and conditional effects. Multivariate Behavioral Research, 51, 374-391, https://10.1080/00273171.2016.1151334