Evaluation of partial least-squares with second-order advantage for the multi-way spectroscopic analysis of complex biological samples in the presence of analyte–background interactions

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
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Biological Samples ◽  
Spectroscopic Analysis ◽  
Second Order

scholarly journals Testing the Youth Physical Activity Promotion Model during the COVID-19 Pandemic, with Partial Least Squares Second-Order Latent Constructs

2021 ◽  
Vol 18 (12) ◽  
pp. 6398
Author(s):  
Elena Druică ◽  
Rodica Ianole-Călin ◽  
Monica Sakizlian ◽  
Daniela Aducovschi ◽  
Remus Dumitrescu ◽  
...  
Keyword(s):  
Physical Activity ◽  
Least Squares ◽  
Partial Least Squares ◽  
Online Survey ◽  
Physical Activity Promotion ◽  
Second Order ◽  
Latent Constructs ◽  
Activity Promotion ◽  
Youth Physical Activity ◽  
Mediating Mechanisms

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.

Correlation coefficient optimization in partial least-squares regression with application to ATR-FTIR spectroscopic analysis

2015 ◽  
Vol 7 (14) ◽  
pp. 5780-5786 ◽  
Author(s):  
Yifang Chen ◽  
Jiemei Chen ◽  
Tao Pan ◽  
Yun Han ◽  
Lijun Yao
Keyword(s):  
Human Serum ◽  
Least Squares ◽  
Partial Least Squares ◽  
Correlation Coefficient ◽  
Partial Least Squares Regression ◽  
Spectroscopic Analysis ◽  
Selection Method ◽  
Least Squares Regression ◽  
Wavelength Selection ◽  
Coefficient Optimization

A wavelength selection method for spectroscopic analysis, named correlation coefficient optimization partial least-squares (CCO-PLS), is proposed, and was successfully employed for reagent-free ATR-FTIR spectroscopic analysis of albumin and globulin in human serum.

Second-Order Advantage Achieved by Unfolded-Partial Least-Squares/Residual Bilinearization Modeling of Excitation−Emission Fluorescence Data Presenting Inner Filter Effects

2006 ◽  
Vol 78 (23) ◽  
pp. 8051-8058 ◽  
Author(s):  
Diego Bohoyo Gil ◽  
Arsenio Muñoz de la Peña ◽  
Juan A. Arancibia ◽  
Graciela M. Escandar ◽  
Alejandro C. Olivieri
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Second Order ◽  
Inner Filter Effects ◽  
Filter Effects
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