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Abteilung Psychologie

© Universität Bielefeld

Leitung der AE06

Prof. Dr. Axel Mayer


														Prof. Dr. Axel Mayer

axel.mayer@uni-bielefeld.de

Telefon
+49 521 106-4521
Telefon Sekr.
+49 521 106-4508
Raum
UHG T4-241
Aktuelle Forschungsthemen

In seiner Forschung interessiert er sich für die Entwicklung neuer Methoden zur Modellierung von Veränderungen in (intensiven) Längsschnittdaten und für die Untersuchung, ob, wie und bei wem eine Intervention, wie z.B. eine psychotherapeutische Behandlung oder ein Gesundheitstraining, wirkt. Seine methodischen Forschungsschwerpunkte liegen in der Entwicklung und Anwendung von Modellen zur Analyse von durchschnittlichen und bedingten (kausalen) Effekten, kausalen Mediationsmodellen, latenten State-Trait-Modellen (für Experience Sampling Daten) und Modellen für latente Veränderungen. Ein wichtiger Aspekt seiner Forschung ist die Entwicklung von benutzerfreundlicher Statistiksoftware, um moderne statistische Methoden und Modelle einem breiteren Publikum zugänglich zu machen.

Publikationen
Projekte

Sprechstunde

Donnerstags von 13:00 - 14:00 Uhr nach Vereinbarung über sekretariat-methodenlehre@uni-bielefel.de

Biography

Axel Mayer obtained his PhD in 2013 from the University of Jena, Germany. In 2014–2016, he was a post-doctoral researcher in the Department of Data Analysis at Ghent University, and in 2016-2020 he was Juniorprofessor at the Department of Psychology, RWTH Aachen University. Currently, he is a professor for Psychological Methods and Evaluation at Bielefeld University. Since 2018, he is president of the European Association of Methodology.

In his research, he is interested in developing new methods 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 and models for latent change. 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.

Selected publications:

• 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

 

Complete list of publications

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