Publikationen von Paolo Ghisletta

Ghisletta, P., & Lindenberger, U. (2005). Exploring structural dynamics within and between sensory and intellectual functioning in old and very old age: Longitudinal evidence from the Berlin Aging Study. Intelligence, 33(6), 555–587. https://doi.org/10.1016/j.intell.2005.07.002

Lövdén, M., Ghisletta, P., & Lindenberger, U. (2005). Social participation attenuates decline in perceptual speed in old and very old age. Psychology and Aging, 20(3), 423–434. https://doi.org/10.1037/0882-7974.20.3.423

Ghisletta, P., & Lindenberger, U. (2004). Static and dynamic longitudinal structural analyses of cognitive changes in old age. Gerontology, 50(1), 12–16. https://doi.org/10.1159/000074383

Lövdén, M., Ghisletta, P., & Lindenberger, U. (2004). Cognition in the Berlin Aging Study (BASE): The first ten years. Aging, Neuropsychology, and Cognition, 11(2-3), 104–133.

Ghisletta, P., & Lindenberger, U. (2003). Age-based structural dynamics between perceptual speed and knowledge in the Berlin Aging Study: Direct evidence for ability dedifferentiation in old age. Psychology and Aging, 18(4), 696–713. https://doi.org/10.1037/0882-7974.18.4.696

Singer, T., Verhaeghen, P., Ghisletta, P., Lindenberger, U., & Baltes, P. B. (2003). The fate of cognition in very old age: Six-year longitudinal findings in the Berlin Aging Study (BASE). Psychology and Aging, 18(2), 318–331. https://doi.org/10.1037/0882-7974.18.2.318

Ghisletta, P. (2014). Recursive partitioning to study terminal decline in the Berlin Aging Study. In J. J. McArdle & G. Ritschard (Eds.), Contemporary issues in exploratory data mining in the behavioral sciences (pp. 405–428). Routledge.

Kotter-Grühn, D., Kleinspehn-Ammerlahn, A., Hoppmann, C. A., Röcke, C., Rapp, M. A., Gerstorf, D., & Ghisletta, P. (2010). Veränderungen im hohen Alter: Zusammenfassung längsschnittlicher Befunde der Berliner Altersstudie. In U. Lindenberger, J. Smith, K. U. Mayer, & P. B. Baltes (Eds.), Die Berliner Altersstudie (3rd ext. ed., pp. 659–689). Akademie Verlag.

von Oertzen, T., Ghisletta, P., & Lindenberger, U. (2010). Simulating statistical power in latent growth curve modeling: A strategy for evaluating age-based changes in cognitive resources. In M. W. Crocker & J. Siekmann (Eds.), Resource-adaptive cognitive processes (pp. 95–117). Springer. https://doi.org/10.1007/978-3-540-89408-7_6

Lindenberger, U., & Ghisletta, P. (2004). Modeling longitudinal changes in old age: From covariance structures to dynamic systems. In R. A. Dixon, L. Bäckman, & L.-G. Nilsson (Eds.), New frontiers in cognitive aging (pp. 199–216). Oxford University Press.