Publications of Andreas M. Brandmaier

Journal Article (66)

2015
Journal Article
von Oertzen, T., Brandmaier, A. M., & Tsang, S. (2015). Structural equation modeling with Ωnyx. Structural Equation Modeling, 22(1), 148–161. https://doi.org/10.1080/10705511.2014.935842
2014
Journal Article
Ghisletta, P., Bäckman, L., Bertram, L., Brandmaier, A. M., Gerstorf, D., Liu, T., & Lindenberger, U. (2014). The Val/Met polymorphism of the Brain-Derived Neurotrophic Factor (BDNF) gene predicts decline in perceptual speed in older adults. Psychology and Aging, 29(2), 384–392. https://doi.org/10.1037/a0035201
2013
Journal Article
Brandmaier, A. M., von Oertzen, T., McArdle, J. J., & Lindenberger, U. (2013). Structural equation model trees. Psychological Methods, 18, 71–86. https://doi.org/10.1037/a0030001
Journal Article
Freund, J., Brandmaier, A. M., Lewejohann, L., Kirste, I., Kritzler, M., Krüger, A., Sachser, N., Lindenberger, U., & Kempermann, G. (2013). Emergence of individuality in genetically identical mice. Science, 340(6133), 756–759. https://doi.org/10.1126/science.1235294
Journal Article
von Oertzen, T., & Brandmaier, A. M. (2013). Optimal study design with identical power: An application of power equivalence to latent growth curve models. Psychology and Aging, 28(2), 414–428. https://doi.org/10.1037/a0031844
2012
Journal Article
Wrzus, C., Brandmaier, A. M., von Oertzen, T., Müller, V., Wagner, G. G., & Riediger, M. (2012). A new approach for assessing sleep duration and postures from ambulatory accelerometry. PLoS ONE, 7(10), Article e48089. https://doi.org/10.1371/journal.pone.0048089

Book Chapter (5)

2023
Book Chapter
Brandmaier, A. M. (in press). Machine learning for mobile sensing data. In M. Mehl, M. Eid, C. Wrzus, G. Harari, & U. Ebner-Priemer (Eds.), Mobile sensing in psychology: Methods and applications. Guilford Press.
Book Chapter
Brandmaier, A. M. (in press). Big data dimensionality reduction. In M. Mehl, M. Eid, C. Wrzus, G. Harari, & U. Ebner-Priemer (Eds.), Mobile sensing in psychology: Methods and applications. Guilford Press.
Book Chapter
Brandmaier, A. M., & Jacobucci, R. C. (2023). Machine learning approaches to structural equation modeling. In R. H. Hoyle (Ed.), Handbook of structural equation modeling (2nd ed., pp. 722–739). Guilford Press.
2018
Book Chapter
Brandmaier, A. M., Driver, C. C., & Voelkle, M. C. (2018). Recursive partitioning in continuous time analysis. In K. van Montfort, J. H. L. Oud, & M. C. Voelkle (Eds.), Continuous time modeling in the behavioral and related sciences (pp. 259–282). Springer.
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