Residual bilinearization combined with kernel-unfolded partial least-squares: A new technique for processing non-linear second-order data achieving the second-order advantage

2010 ◽  
Vol 100 (2) ◽  
pp. 127-135 ◽  
Author(s):  
Alejandro García-Reiriz ◽  
Patricia C. Damiani ◽  
Alejandro C. Olivieri
Author(s):  
Elena Druică ◽  
Rodica Ianole-Călin ◽  
Monica Sakizlian ◽  
Daniela Aducovschi ◽  
Remus Dumitrescu ◽  
...  

We tested the Youth Physical Activity Promotion (YPAP) framework on Romanian students in order to identify actionable determinants to support participation in physical activity. Our sample consisted of 665 responses to an online survey, with participants aged 18–23 (mean = 19 years); 70% were women. We used the partial least squares algorithm to estimate the relationships between students’ behavior and possible predictors during the COVID-19 pandemic. Our results indicate that all the theoretical dimensions of YPAP (predisposing, enabling and reinforcing) have a positive and significant impact on physical activity, with two mediating mechanisms expressed as predisposing factors: able and worth. Unlike previous research, we used second-order latent constructs, unveiling a particular structure for the enabling dimension that only includes sport competence, fitness and skills, but not the environmental factors.


The Analyst ◽  
2006 ◽  
Vol 131 (6) ◽  
pp. 718-723 ◽  
Author(s):  
María J. Culzoni ◽  
Héctor C. Goicoechea ◽  
Ariana P. Pagani ◽  
Miguel A. Cabezón ◽  
Alejandro C. Olivieri

The Analyst ◽  
1998 ◽  
Vol 123 (3) ◽  
pp. 483-488 ◽  
Author(s):  
J. J. Berzas Nevado ◽  
M. A. Gómez Laguna ◽  
J. A. Murillo Pulgarín ◽  
J. Amador-Hernández ◽  
M. A. Gómez Laguna

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