Match!
Andreas M. Brandmaier
Max Planck Society
42Publications
12H-index
481Citations
Publications 42
Newest
#1Julian David Karch (LEI: Leiden University)H-Index: 2
#2Julian D. Karch (LEI: Leiden University)
Last.Andreas M. Brandmaier (MPG: Max Planck Society)H-Index: 12
view all 10 authors...
Abstract Adequate reliability of measurement is a precondition for investigating individual differences and age-related changes in brain structure. One approach to improve reliability is to identify and control for variables that are predictive of within-person variance. To this end, we applied both classical statistical methods and machine-learning-inspired approaches to structural magnetic resonance imaging (sMRI) data of six participants aged 24–31 years gathered at 40–50 occasions distribute...
#1Sezen Cekic (University of Geneva)H-Index: 5
#2Stephen R. AicheleH-Index: 12
Last.Paolo GhislettaH-Index: 27
view all 5 authors...
In biostatistics and medical research, longitudinal data are often composed of repeated assessments of a variable (e.g., blood pressure or other biomarkers) and dichotomous indicators to mark an event of interest (e.g., recovery from disease, or death). Consequently, joint modeling of longitudinal and time-to-event data has generated much interest in these disciplines over the previous decade. In psychology, too, often we are interested in relating individual trajectories (e.g., cognitive perfor...
#1Simone Kühn (MPG: Max Planck Society)H-Index: 40
#2Sandra Düzel (MPG: Max Planck Society)H-Index: 10
Last.Keith F. Widaman (UCR: University of California, Riverside)H-Index: 58
view all 8 authors...
The fact that tyrosine increases dopamine availability that, in turn, may enhance cognitive performance has led to numerous studies on healthy young participants taking tyrosine as a food supplement. As a result of this dietary intervention, participants show performance increases in working memory and executive functions. However, the potential association between habitual dietary tyrosine intake and cognitive performance has not been investigated to date. The present study aims at clarifying t...
#1Ross Jacobucci (ND: University of Notre Dame)H-Index: 5
#2Andreas M. Brandmaier (MPG: Max Planck Society)H-Index: 12
Last.Rogier A. Kievit (Cognition and Brain Sciences Unit)H-Index: 20
view all 3 authors...
R. A. Kievit is supported by the Sir Henry Wellcome Trust (Grant 107392/Z/15/Z) and by an MRC Programme Grant (SUAG/014/RG91365). This project has also received funding from the European Union’s Horizon 2020 Research and Innovation program (Grant 732592).
#1Elliot M. Tucker-Drob (University of Texas at Austin)H-Index: 27
#2Andreas M. Brandmaier (MPG: Max Planck Society)H-Index: 12
Last.Ulman Lindenberger (MPG: Max Planck Society)H-Index: 77
view all 3 authors...
#1Manuel Arnold (MPG: Max Planck Society)
Last.Manuel C. Voelkle (MPG: Max Planck Society)H-Index: 12
view all 4 authors...
#1Andrew Bender (MSU: Michigan State University)
#2Andreas M. Brandmaier (MPG: Max Planck Society)H-Index: 12
Last.Simone Kühn (MPG: Max Planck Society)H-Index: 40
view all 7 authors...
Age-related memory impairments have been linked to differences in structural brain parameters, including cerebral white matter (WM) microstructure and hippocampal (HC) volume, but their combined influences are rarely investigated. In a population-based sample of 337 older participants (Mage=69.66, SDage=3.92 years) we modeled the independent and joint effects of limbic WM microstructure and HC subfield volumes on verbal learning. Participants completed a verbal learning task over five learning t...
#1Andreas M. Brandmaier (MPG: Max Planck Society)H-Index: 12
#2Elisabeth Wenger (MPG: Max Planck Society)H-Index: 11
Last.Ulman Lindenberger (MPG: Max Planck Society)H-Index: 77
view all 6 authors...
#1Andreas M. Brandmaier (MPG: Max Planck Society)H-Index: 12
#2Timo von Oertzen (MPG: Max Planck Society)H-Index: 19
Last.Christopher Hertzog (MPG: Max Planck Society)H-Index: 57
view all 5 authors...
Latent Growth Curve Models (LGCM) have become a standard technique to model change over time. Prediction and explanation of inter-individual differences in change are major goals in lifespan research. The major determinants of statistical power to detect individual differences in change are the magnitude of true inter-individual differences in linear change (LGCM slope variance), design precision, alpha level, and sample size. Here, we show that design precision can be expressed as the inverse o...
1234