Hernández, M. V., Colmenares, F., & Arias, R. M. 2003. Application of hierarchical linear modelling to the study of trajectories of behavioural development. Animal Behaviour, 66, 607–613

2004 ◽  
Vol 67 (2) ◽  
pp. 367
Author(s):  
M.V Hernández ◽  
F Colmenares ◽  
R.M Arias
Keyword(s):  
Animal Behaviour ◽  
Behavioural Development ◽  
Hierarchical Linear Modelling ◽  
Linear Modelling

Application of hierarchical linear modelling to the study of trajectories of behavioural development

2003 ◽  
Vol 66 (3) ◽  
pp. 607-613 ◽  
Author(s):  
Marı́a Victoria Hernández-Lloreda ◽  
Fernando Colmenares ◽  
Rosario Martı́nez Arias
Keyword(s):  
Behavioural Development ◽  
Hierarchical Linear Modelling ◽  
Linear Modelling

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.

Individual Management and Counseling as Moderators in Achieving Career Competencies and Success

2014 ◽  
Vol 42 (5) ◽  
pp. 869-880 ◽  
Author(s):  
Huo-Tsan Chang ◽  
Chia-Yi Feng ◽  
Chi-Lih Shyu
Keyword(s):  
Career Counseling ◽  
Organizational Support ◽  
Career Success ◽  
Self Regulation ◽  
Career Management ◽  
Manufacturing Companies ◽  
Hierarchical Linear Modelling ◽  
Linear Modelling ◽  
The Relationship ◽  
Career Competencies

We adopted the perspectives of organizational support and self-regulation to examine how counseling and individual management, respectively, moderate career competencies to predict career success. Hierarchical linear modelling was conducted with 604 employees and 217 managers of 26 manufacturing companies in Taiwan. As we predicted, our results showed that career competencies were positively related to career success. Also, career counseling and individual career management were found to have a moderating effect on the relationship between career competencies and subjective career success. Implications and limitations of the findings are discussed.

The Impact of Neighborhood Characteristics on Housing Prices-An Application of Hierarchical Linear Modeling

2012 ◽  
Vol 1 (2) ◽  
pp. 31-44
Author(s):  
Lee Chun Chang ◽  
Hui-Yu Lin
Keyword(s):  
Empirical Study ◽  
Hierarchical Linear Modeling ◽  
House Prices ◽  
Housing Prices ◽  
Neighborhood Characteristics ◽  
Linear Modeling ◽  
Hierarchical Linear Modelling ◽  
Neighborhood Characteristic ◽  
Linear Modelling ◽  
The Impact

Housing data are of a nested nature as houses are nested in a village, a town, or a county. This study thus applies HLM (hierarchical linear modelling) in an empirical study by adding neighborhood characteristic variables into the model for consideration. Using the housing data of 31 neighborhoods in the Taipei area as analysis samples and three HLM sub-models, this study discusses the impact of neighborhood characteristics on house prices. The empirical results indicate that the impact of various neighborhood characteristics on average housing prices is different and that the impact of house characteristics on house prices is also moderated by neighborhood characteristics.

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