Self-determined motivation, emotional process and subjective performance among young elite athletes: A longitudinal hierarchical linear modelling approach

2020 ◽  
Vol 20 (9) ◽  
pp. 1255-1267
Author(s):  
Valérian Cece ◽  
Maxime Duchesne ◽  
Emma Guillet-Descas ◽  
Guillaume Martinent
Keyword(s):  
Elite Athletes ◽  
Hierarchical Linear Modelling ◽  
Emotional Process ◽  
Linear Modelling ◽  
Modelling Approach

scholarly journals Association between obesity in 4‐ to 7‐year‐old children and eight types of crime: a hierarchical linear modelling approach

2018 ◽  
Vol 5 (2) ◽  
pp. 159-167
Author(s):  
K. M. Benzies ◽  
M. T. Yates ◽  
A. B. Patel ◽  
A. R. Afzal ◽  
J. Kurilova ◽  
...  
Keyword(s):  
Hierarchical Linear Modelling ◽  
Linear Modelling ◽  
Modelling Approach

scholarly journals LIMO EEG: A Toolbox for Hierarchical LInear MOdeling of ElectroEncephaloGraphic Data

2011 ◽  
Vol 2011 ◽  
pp. 1-11 ◽  
Author(s):  
Cyril R. Pernet ◽  
Nicolas Chauveau ◽  
Carl Gaspar ◽  
Guillaume A. Rousselet
Keyword(s):  
Hierarchical Linear Modeling ◽  
Response Variability ◽  
Evoked Responses ◽  
Single Trial ◽  
Linear Modeling ◽  
Matlab Toolbox ◽  
Hierarchical Linear Modelling ◽  
Space And Time ◽  
Brain Responses ◽  
Linear Modelling

Magnetic- and electric-evoked brain responses have traditionally been analyzed by comparing the peaks or mean amplitudes of signals from selected channels and averaged across trials. More recently, tools have been developed to investigate single trial response variability (e.g., EEGLAB) and to test differences between averaged evoked responses over the entire scalp and time dimensions (e.g., SPM, Fieldtrip). LIMO EEG is a Matlab toolbox (EEGLAB compatible) to analyse evoked responses over all space and time dimensions, while accounting for single trial variability using a simple hierarchical linear modelling of the data. In addition, LIMO EEG provides robust parametric tests, therefore providing a new and complementary tool in the analysis of neural evoked responses.

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