Combining the advantages of multilevel and orthogonal partial least squares data analysis for longitudinal metabolomics: Application to kidney transplantation

Abstract The pyrolysis (Py)-GC-MS technique was first introduced for the identification of two kinds of Chinese geographical indication vinegars because its advantages are that it is a simple and convenient sample pretreatmentand inlet method. Abundant Py information about vinegars was obtained using Py-GC-MS; 21 common peaks were selected. With the help of the classical partial least-squares (PLS) modeling method for data analysis, two identification models for Shanxi extra-aged (SX) and Zhenjiang (ZJ) vinegars were established, respectively. An N-reducing method was used to select the variables. The variables were reduced one at a time to build the PLS models with the lowest number of misjudgments. Both models had good recognition rates, identifying over 90% of samples correctly. Thus, combining Py-GC-MS and PLS could be regarded as an effective method for the identification of SX and ZJ vinegars.

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Effect of SME Food Entrepreneurs Knowledge on Halal Certification for Certified Awareness Using Partial Least Square

Jurnal Teknik Industri ◽

10.22219/jtiumm.vol20.no2.36-47 ◽

2019 ◽

Vol 20 (2) ◽

pp. 36

Author(s):

Ida Giyanti ◽

Erna Indriastiningsih

Keyword(s):

Data Analysis ◽

Least Squares ◽

Partial Least Squares ◽

Structural Equation Model ◽

Structural Equation ◽

Equation Model ◽

The Other ◽

Medium Enterprise ◽

The Impact ◽

Comprehension Rate

This study aims to predict the impact of the understanding of halal certification by Small Medium Enterprise (SME) entrepreneurs on the intention to conduct halal certification. This study was conducted in the Cooperative and SME Office of Surakarta City. The Halal Certification Comprehension Rate was assessed using three variables. We had knowledge of halal (PGT), perceived halal certification advantages (MNF), and perceived halal certification procedures (PROS). Structural Equation Model-Partial Least Squares (SEM-PLS) was used for data analysis. The results show that SMEs have a good knowledge of halal and agree that halal certification is beneficial to their businesses. We found, though, that the processes for handling Halal Certification are relatively complex. Based on the study, the perception of Halal Certification Benefits (MNF) is significantly affected by the intention of SMEs to conduct Halal Certification (NHL). The other two results show a positive correlation. However, they are not statistically significant.This study aims to predict the impact of the understanding of halal certification by Small Medium Enterprise (SME) entrepreneurs on the intention to conduct halal certification. This study was conducted in the Cooperative and SME Office of Surakarta City. The Halal Certification Comprehension Rate was assessed using three variables. We had knowledge of halal (PGT), perceived halal certification advantages (MNF), and perceived halal certification procedures (PROS). Structural Equation Model-Partial Least Squares (SEM-PLS) was used for data analysis. The results show that SMEs have a good knowledge of halal and agree that halal certification is beneficial to their businesses. We found, though, that the processes for handling Halal Certification are relatively complex. Based on the study, the perception of Halal Certification Benefits (MNF) is significantly affected by the intention of SMEs to conduct Halal Certification (NHL). The other two results show a positive correlation, but they are not statistically significant.

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PLS-SEM STATISTICAL PROGRAMS: A REVIEW

Journal of Applied Structural Equation Modeling ◽

10.47263/jasem.5(1)06 ◽

2021 ◽

Vol 5 (1) ◽

pp. i-xiv

Author(s):

Mumtaz Ali Memon ◽

T. Ramayah ◽

Jun-Hwa Cheah ◽

Hiram Ting ◽

Francis Chuah ◽

...

Keyword(s):

Structural Equation Modeling ◽

Data Analysis ◽

Least Squares ◽

Partial Least Squares ◽

Multivariate Data Analysis ◽

Structural Equation ◽

Multivariate Data ◽

Informed Decision ◽

Equation Modeling

Partial least squares structural equation modeling (PLS-SEM) is one of the most widely used methods of multivariate data analysis. Although previous research has discussed different aspects of PLS-SEM, little is done to explain the attributes of the different PLS-SEM statistical applications. The objective of this editorial is to discuss a variety of PLS-SEM applications, including SmartPLS, WarpPLS, and ADANCO. It is written based on information received from the developers via emails as well as our ongoing understanding and experience of using these applications. We hope this editorial can serve as a manual for users to understand the unique characteristics of each PLS-SEM application and make an informed decision on the most appropriate application in their research.

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