scholarly journals The Implementation of Nonlinear Principal Component Analysis to Acquire the Demography of Latent Variable Data (A Study Case on Brawijaya University Students)

2020 ◽  
Vol 8 (4) ◽  
pp. 437-442
Author(s):  
Solimun Solimun ◽  
Adji Achmad Rinaldo Fernandes ◽  
Retno Ayu Cahyoningtyas
Keyword(s):  
Principal Component Analysis ◽  
University Students ◽  
Latent Variable ◽  
Principal Component ◽  
Component Analysis ◽  
Nonlinear Principal Component Analysis ◽  
Study Case ◽  
Variable Data

Attitudes of French-Canadian University Students toward Use of Condoms: A Structural Analysis

1989 ◽  
Vol 65 (3) ◽  
pp. 851-854 ◽  
Author(s):  
Jean Bernard ◽  
Yves Hébert ◽  
Anton de Man ◽  
David Farrar
Keyword(s):  
Principal Component Analysis ◽  
Structural Analysis ◽  
University Students ◽  
Principal Component ◽  
Component Analysis ◽  
Sexual Pleasure ◽  
French Canadian ◽  
General Attitude

164 French-Canadian university students took part in a study analyzing the factorial pattern of attitudes toward the use of condoms. A principal component analysis identified 7 factors, namely, positive general attitude toward use of condoms, contraceptive security, inhibition of sexual pleasure, inconvenience, embarrassment, responsibility, and lessening of physical pleasure.

scholarly journals Principal Component Analysis of the Potential for Increased Rail Competitiveness in East-Central Europe

2019 ◽  
Vol 11 (15) ◽  
pp. 4181 ◽  
Author(s):  
Szabolcs Duleba ◽  
Bálint Farkas
Keyword(s):  
Principal Component Analysis ◽  
Latent Variable ◽  
Structural Changes ◽  
Principal Component ◽  
Component Analysis ◽  
Factor Space ◽  
Market Liberalization ◽  
East Central Europe ◽  
East Central ◽  
Rail Freight

Increased rail competitiveness has been the objective of many countries around the world, including member states of the EU. Although railway market liberalization has always been accompanied by high expectations of increased efficiency and competitiveness, the overall impact of such decisions can be considered controversial. This paper aims to contribute to the scientific debate by conducting a factor analysis of some East-Central European countries from the aspect of rail freight competitiveness. Since many highly correlated factors influence competitiveness, its mathematical–statistical representation and analysis is difficult due to the high number of dimensions of the factor space. Moreover, competitiveness cannot be measured directly only as a latent variable which is a feature of Principal Component Analysis (PCA). The introduced PCA, model by way of reducing the number of dimensions, can highlight the relations among the attributes and determine the most crucial issues capable of increasing rail competitiveness in the given countries and also of clustering those national railway markets. Recommendations for structural changes in national rail freight markets of the region are also supplied. Our results show that international rail competitiveness depends rather on market efficiency than on market liberalization due to the fact that the Global Competitiveness Index and Export/Import attributes did not significantly correlate with market concentration. As for the larger domestic rail freight sectors, small freight forwarders—spawned by liberalization—are shown to play a significant role in increasing competitiveness.

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