Publikationen von Timo von Oertzen

Bauer, T. A., Folster, A., Braun, T., & von Oertzen, T. (2021). A group comparison test under uncertain group membership. Psychometrika, 86(4), 920–937. https://doi.org/10.1007/s11336-021-09794-x

Braun, T., & von Oertzen, T. (2021). Empathy, cognitive functioning, and prosocial behavior in mentored children. New Directions for Child and Adolescent Development, 2021(179), 41–57. https://doi.org/10.1002/cad.20409

Fitzgerald, C. E., Estabrook, R., Martin, D. P., Brandmaier, A. M., & von Oertzen, T. (2021). Correcting the bias of the root mean squared error of approximation under missing data. Methodology, 17(3), 189–204. https://doi.org/10.5964/meth.2333

Brandmaier, A. M., Ghisletta, P., & von Oertzen, T. (2020). Optimal planned missing data design for linear latent growth curve models. Behavior Research Methods, 52, 1445–1458. https://doi.org/10.3758/s13428-019-01325-y

Braun, T., Kruse, J., Singleton, J., Hiemeyer, B., & von Oertzen, T. (2020). Effects of youth mentoring on depressive symptoms of single mothers. Global Journal of Community Psychology Practice, 11(3), Article 219.

Ghisletta, P., Mason, F., von Oertzen, T., Hertzog, C., Nilsson, L.-G., & Lindenberger, U. (2020). On the use of growth models to study normal cognitive aging. International Journal of Behavioral Development, 44(1), 88–96. https://doi.org/10.1177/0165025419851576

Schmiedek, F., Lövdén, M., von Oertzen, T., & Lindenberger, U. (2020). Within-person structures of daily cognitive performance differ from between-person structures of cognitive abilities. PeerJ, 8, Article e9290. https://doi.org/10.7717/peerj.9290

Stefan, A. M., & von Oertzen, T. (2020). Bayesian power equivalence in latent growth curve models. British Journal of Mathematical and Statistical Psychology, 73(S1), 180–193. https://doi.org/10.1111/bmsp.12193

von Oertzen, T., Schmiedek, F., & Voelkle, M. C. (2020). Ergodic subspace analysis. Journal of Intelligence, 8(1), Article 3. https://doi.org/10.3390/jintelligence8010003

Meyer, P., Schophaus, F. M., Glassen, T., Riedl, J., Rohrer, J. M., Wagner, G. G., & von Oertzen, T. (2019). Using the Dirichlet process to form clusters of people's concerns in the context of future party identification. PLoS ONE, 14(3), Article e0212944. https://doi.org/10.1371/journal.pone.0212944