scholarly journals Assessment of PLS-SEM Path Model for Coefficient of Determination and Predictive Relevance of Consumer Trust on Organic Cosmetics

2016 ◽  
Vol 15 (4) ◽  
pp. 1-19
Author(s):  
Suhan . ◽  
Anantha Padmanabha Achar
Keyword(s):  
Latent Variables ◽  
Latent Variable ◽  
Quantitative Research ◽  
Direct Relationship ◽  
Threshold Value ◽  
Path Model ◽  
Coefficient Of Determination ◽  
Path Coefficient ◽  
Threshold Values ◽  
Research Survey

In this paper the researchers investigated the coefficient of determination R-Square and predictive relevance (Q2) through Blindfolding. To fulfil the aim of the study, a structured quantitative research survey has been conducted with 640 sample size. The results emerged from the research survey shows that the R-Square hasmoderate strength for the endogenous latent variable trust and substantial strength or effect for the endogenous latent variables integrity, ability and benevolence. After calculating Q2for the endogenous latent variable ability, benevolence, integrity and trust it was found that the model has predictive relevance for these constructs. The path coefficient threshold values for measuring between indicators namely, cause purview and emotional benefits, cause consequential and trust, cause rubric and trust, cause span and emotional benefits, emotional benefits and trust, functional benefits and trust, ability and trust, benevolence and trust and also for integrity and trust are above the threshold value of 1.96 substantiate the hypothesis and exerts direct relationship between two variables. But the path coefficient threshold values between indicators namely, Cause purview and trust, cause consequential and trust, cause rubric and emotional benefits, cause span and trust, and also self-expressive and trust are below the threshold value of 1.96 does not substantiate the hypothesis and also does not exerts direct relationship between two variables. At the end of the paper, the author highlights the results, along with implications and limitations.

Conceptualizing Protective Family Context and Its effect on Substance Use: Comparisons Across Diverse Ethnic-Racial Youth

2019 ◽  
Author(s):  
Kevin Constante ◽  
Edward Huntley ◽  
Emma Schillinger ◽  
Christine Wagner ◽  
Daniel Keating
Keyword(s):  
Substance Use ◽  
Measurement Invariance ◽  
Latent Variables ◽  
Latent Variable ◽  
Path Model ◽  
Family Context ◽  
Partial Metric ◽  
Racial Groups ◽  
Protective Methods ◽  
Family Variables

Background: Although family behaviors are known to be important for buffering youth against substance use, research in this area often evaluates a particular type of family interaction and how it shapes adolescents’ behaviors, when it is likely that youth experience the co-occurrence of multiple types of family behaviors that may be protective. Methods: The current study (N = 1716, 10th and 12th graders, 55% female) examined associations between protective family context, a latent variable comprised of five different measures of family behaviors, and past 12 months substance use: alcohol, cigarettes, marijuana, and e-cigarettes. Results: A multi-group measurement invariance assessment supported protective family context as a coherent latent construct with partial (metric) measurement invariance among Black, Latinx, and White youth. A multi-group path model indicated that protective family context was significantly associated with less substance use for all youth, but of varying magnitudes across ethnic-racial groups. Conclusion: These results emphasize the importance of evaluating psychometric properties of family-relevant latent variables on the basis of group membership in order to draw appropriate inferences on how such family variables relate to substance use among diverse samples.

scholarly journals Using psychometric data from the stated preference (SP) experiments to search explanatory power for appropriateness of congestion charging policy

2016 ◽  
Vol 5 (3) ◽  
Author(s):  
Sofyan M. Saleh ◽  
Sugiarto Sugiarto ◽  
Cut Mutiawati ◽  
Renni Angraini ◽  
Muhammad Isya
Keyword(s):  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Stated Preference ◽  
Explanatory Power ◽  
Path Coefficient ◽  
Annual Income ◽  
Positive Correlation ◽  
Psychological Determinants ◽  
Psychometric Data

Comprehensive stated preference (SP) experiment was conducted in Jakarta (a capital of Indonesia), where proposal for congestion charge (CC) has been considered as a way to reduce acute traffic congestion. With the government planning a CC scheme, public support is regarded as a prerequisite for its implementation. Therefore, a framework of structural equation model (SEM) is used to search explanatory power for the appropriateness of CC considering unobserved variable (latent variable) from psychometric data obtained from SP questionare.  Causal paths among psychological determinants and their strength are measured and analyzed along with proposal acceptability from a psychological perspective. The findings from analysis with a SEM approach shows that a number of psychological determinants provide an explanation for the acceptability of the proposed scheme. The findings from analysis with a SEM approach shows that a number of psychological determinants provide an explanation for the appropriateness of the proposed scheme. Latent variables representing the validity of the CC scheme, such as ACE, APC and REC appear to have a significant explanation. These emerge as psychological determinants contributing a positive correlation with enhancement of appropriateness CC policy. Empirical result further shows that males have positive scores for the latent variables of car dependency (CDC) and inhibition freedom of movement (IFM). Furthermore, the variable of annual income, it has a positive correlation with recognition of the effects of CC in mitigating congestion and environmental problems (REC), car dependency (CDC) and awareness of the problems of cars in society (APC). This means that respondents with higher incomes are more concerned with the problems manifested by motorization while, on the contrary, the path coefficient between annual income (AI) and car dependency (CDC) has a value of 0.270. This discloses an automobile dependency. These findings should provide insight that designing a more acceptable policy in respecting to the acceptance of public in large.

scholarly journals Agents Affecting the Productivity of Pine Plantations on the Loess Plateau in China: A Study Based on Structural Equation Modeling

Forests ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1328
Author(s):  
Xuan Zhao ◽  
Yanjie Li ◽  
Hao Song ◽  
Yuhuan Jia ◽  
Jianjun Liu
Keyword(s):  
Indirect Effect ◽  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Equation Modeling ◽  
Path Coefficient ◽  
Site Conditions ◽  
Population Stability ◽  
Forest Density ◽  
Weight Value

Stability and productivity are important indicators used to measure the state of forest ecosystems. Artificial forests populations with reasonable structures and strong stability are critical for ecosystem productivity. Previous studies have focused on individual factors, while the mechanisms of how multiple factors affect population productivity remain unknown. We used 57 plots in a Chinese pine (Pinus tabuliformis) plantation to investigate 23 stand factors and analyzed the relationships among site factors, population structure, population stability, and population productivity using partial least square-structural equation modeling (PLS-SEM). The results showed that the population productivity of the plantation was directly affected by the population stability latent variable but indirectly affected by the site conditions latent variables (indirect effect path coefficient = 0.249) and forest structure (indirect effect path coefficient = 0.222). However, the site conditions latent variable was the main factor directly affecting the population stability latent variables; the total effect was 0.511 (direct effect path coefficient = 0.307, indirect effect path coefficient = 0.204), and the influence of forest structure on population stability was lower than that of the site conditions latent variable (direct effect path coefficient = 0.454). The factor with the greatest weight among the site conditions latent variable was slope (0.747), indicating that slope contributes the most to latent variables related to forest population stability. Among all variables affecting the forest stability latent variables, forest density had the highest weight value (0.803), and the weight value of forest mortality was lower than that of forest density. The weights of the latent variables associated with population structure from high to low were canopy density, the uniform angle index, and the spatial competition index, indicating that competition for space had the lowest influence on the population stability latent variables. The results provide new insights and ideas for quantifying relationships among different driving factors and a basis for scientific and rational plantation management.

scholarly journals HUBUNGAN AKREDITASI DAN UJIAN NASIONAL PADA SEKOLAH NEGERI DENGAN GENERALIZED STRUCTURED COMPONENT ANALYSIS

2019 ◽  
Vol 3 (3) ◽  
pp. 260-271
Author(s):  
Rezi Wahyuni ◽  
Budi Susetyo ◽  
Anwar Fitrianto
Keyword(s):  
Public Schools ◽  
Education System ◽  
Latent Variables ◽  
Latent Variable ◽  
Goodness Of Fit ◽  
Educational Institution ◽  
Component Analysis ◽  
Equation Modeling ◽  
Path Coefficient ◽  
Generalized Structured Component Analysis

There are several views and tendencies that distinguish between schools and madrasas in several aspects, one of them is the curriculum. Madrasah as islamic educational institution contains more religious lessons compared to public schools. As a result, madrasah are considered less able to provide good result in educational achievement. Overall, the education system which is based on National Education Standards (SNP) is used for assessing the educational accreditation. SNP is the minimum criterion of education system in Indonesia can be evaluated from the National Examination (UN). As latent variable, SNP is measured through 124 items as variable indicators. One of methods which is used to measure the relationship among latent variables, and latent variables with their indicator variables is structural equation modeling (SEM). A component-based SEM is called Generalized Structured Component Analysis (GSCA). GSCA analysis based on measurement model, there were 9 indicators were not significant, in which 1 indicator of standard of education and staff (SPT), 5 indicators on standard of infrastructure (SSP), and 3 indicators on standard of cost (SB). Evaluation of the structural model, it was found that the path coefficient of standard of content (SI) to UN was not significant and standard of competency (SKL) given the biggest direct effect to UN. The overall goodness of fit model showed that the total variance that can be explained of all indicators and latent variables in evaluating model of accreditation and national examinations was 63.9%. The difference in the percentage of accreditation status between schools and madrasas shows different UN results. In the 2017-2018 period, MTsN had a higher percentage of accredited schools, in line with that the average MTsN UN obtained was better than that of SMP in all types of subjects.

The Relationship Between Performance Measures and Overall Performance in the Manufacturing Environment

2021 ◽  
pp. 341-354
Author(s):  
Raman Kumar ◽  
Harwinder Singh
Keyword(s):  
Performance Measures ◽  
Latent Variables ◽  
Manufacturing Industry ◽  
Northern Region ◽  
Performance Measure ◽  
Path Model ◽  
Path Coefficient ◽  
Confirmatory Factor ◽  
Overall Performance ◽  
Manufacturing Organization

The overall performance of a manufacturing organization can be enhanced by thoroughly examine and monitor the activities of all departments such as production, inventory, maintenance, etc. involved in the manufacturing system. The present study highlights the relationships between different performance measure and overall performance from the perspective of the agricultural tool manufacturing industry. A path model consists of 13 observed variables, and four performance measures (latent variables) was developed and tested using SPSS software package and AMOS 21. The outcome of the present work is reflected by the respondent of 105 valid questionnaires who are occupied with agriculture tool manufacturing firms situated in the northern region of India. The outcome of confirmatory factor analysis showed that operational performance has higher path coefficient. The limitation of this work is that the findings are applicable to the specific sector of manufacturing industry only.

scholarly journals PENGARUH BERPIKIR KRITIS TERHADAP HASIL BELAJAR MATEMATIKA

2020 ◽  
Vol 3 (1) ◽  
pp. 38-41
Author(s):  
Resti Saputri ◽  
Nintin Nurlela ◽  
Yuyun Elizabeth Patras
Keyword(s):  
Critical Thinking ◽  
Learning Outcomes ◽  
Quantitative Research ◽  
Mathematics Learning ◽  
Positive Influence ◽  
Coefficient Of Determination ◽  
Path Coefficient ◽  
Research Approach ◽  
Average Value ◽  
And Mathematics

THE EFFECT OF CRITICAL THINKING ON MATHEMATICS LEARNING OUTCOMESThis research was conducted using an associative quantitative research approach with a type of causal approach consisting of two variables namely critical thinking as an independent variable and mathematics learning outcomes as the dependent variable. The main objective of this research is to find out the positive influence between critical thinking and mathematics learning outcomes. The subjects of this study were students of class IV-A. IV-B, and IV-C. Bogor City Pondok Rumput Elementary School consisting of 49 respondents. The research was carried out in the first semester of the 2019/2020 school year. The instrument validity test uses the Person Product Moment correlation formula and the reliability test uses the Cronbach Alpha formula. Test data analysis requirements using the test for normality, homogeneity, and linearity. The average value on the critical thinking variable was 109.7 and the average value on the mathematics learning variable was 68.1. Then the results of the study showed that there was an influence of critical thinking on mathematics learning outcomes, indicated by statistical analysis that produced a path coefficient (pxy) value of 0.64. This shows the influence of critical thinking on mathematics learning outcomes, while the coefficient of determination (r2) of 0.409 or 40.9%. This means the value of the influence of critical thinking on mathematics learning outcomes of 40.9%, through the regression equation The remaining 59.1% is determined by other factors. Based on the results of the research above, it can be concluded that there is a positive influence between critical thinking on students' mathematics learning outcomes. This means that one of the factors in mathematics learning outcomes is due to students' critical thinking at the time of learning.

scholarly journals Structural Causality Between National Examination Score and The School Accreditation Categories

2022 ◽  
Vol 8 (1) ◽  
pp. 73-78
Author(s):  
Anwar Fitrianto ◽  
Budi Susetyo ◽  
Iswan Achlan Setiawan
Keyword(s):  
Academic Achievement ◽  
Causal Relationship ◽  
Latent Variable ◽  
Goodness Of Fit ◽  
Structural Model ◽  
Educational Theory ◽  
Coefficient Of Determination ◽  
Path Coefficient ◽  
Ministry Of Education ◽  
National Education

This study aims to compare and determine the best model to describe the relationship between National Education Standard (NES) and CBNE scores using generalized structured component analysis. Model 1 describes the causal relationship between the NES and CBNE based on the educational theory of the Ministry of National Education and the Ministry of Religion (2010), Model 2 describes the causal relationship between the NES and CBNE based on the educational theory of the Ministry of Education and Culture (2012), and Model 3 describes the causal relationship between the NES and CBNE based on the educational theory of the Ministry of Education and Culture (2017). The results of the structural model evaluation have found that in Model 1, the SI path coefficient to Academic Achievement (PA) is not significant, in Model 2, the SI path coefficient to PA and SPT to SPN is not significant and in Model 3, the SI path coefficient to PA is also not significant. The coefficient of determination of each endogenous latent variable for each model ranges from 0.20 - 0.75. While the resulting Q-square value for all models is more than 0.9 to represent very good predictive relevance. Based on the overall goodness of fit, it is found that Model 3 produces the largest FIT and AFIT values. So it can be said that model 3 is better than other models. This model produces 11 invalid indicator variables, namely points 17, 39, 51, 55, 57, 59, 73, 75, 76, 80, and 108. The study found that National Education Standards that significantly affect academic achievement are graduate competency standards, process standards, and educational assessment standards

Probability-Based and Measurement-Related Hypotheses With Full Restriction for Investigations by Means of Confirmatory Factor Analysis

Methodology ◽  
2011 ◽  
Vol 7 (4) ◽  
pp. 157-164
Author(s):  
Karl Schweizer
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Cognitive Processing ◽  
Latent Variables ◽  
Repeated Measures ◽  
Latent Variable ◽  
Model Fit ◽  
Repeated Measures Data ◽  
Confirmatory Factor ◽  
And Performance

Probability-based and measurement-related hypotheses for confirmatory factor analysis of repeated-measures data are investigated. Such hypotheses comprise precise assumptions concerning the relationships among the true components associated with the levels of the design or the items of the measure. Measurement-related hypotheses concentrate on the assumed processes, as, for example, transformation and memory processes, and represent treatment-dependent differences in processing. In contrast, probability-based hypotheses provide the opportunity to consider probabilities as outcome predictions that summarize the effects of various influences. The prediction of performance guided by inexact cues serves as an example. In the empirical part of this paper probability-based and measurement-related hypotheses are applied to working-memory data. Latent variables according to both hypotheses contribute to a good model fit. The best model fit is achieved for the model including latent variables that represented serial cognitive processing and performance according to inexact cues in combination with a latent variable for subsidiary processes.

IMPACT OF AIS AND STRESSED OUT AN EMPLOYEES TO THEIR PERFORMANCE AT PT EFRATA RETAILINDO

2019 ◽  
Vol 5 (1) ◽  
pp. 22-30
Author(s):  
Wiwit Ayu Retno Sari ◽  
Suhendro Suhendro ◽  
R. Riana Dewi
Keyword(s):  
Information Systems ◽  
Work Stress ◽  
Quantitative Research ◽  
Linear Regression Analysis ◽  
Accounting Information ◽  
Multiple Linear Regression Analysis ◽  
Primary Data ◽  
Coefficient Of Determination ◽  
Accounting Information System ◽  
Accounting Information Systems

This research aims to test the influence of accounting information system and work stress on performance of employees of PT Efrata Retailindo. The type of research used in this research is quantitative research. The source of the data in the research is primary data. The population in this study are all employees of PT Efrata Retailindo totalling 47 people. Sampling techniques in the study using a purposive sample. While the data collection method used is to use the questionnaire to all employees of PT Efrata Retailindo. Data analysis techniques using multiple linear regression analysis. Based on the results of the study it can be concluded that work stress had no effect on performance of employees of PT Efrata Retailindo, while information systems accounting effect on the performance of the employees of PT Efrata Retailindo. The value of the coefficient of determination (R2) amounting to 0.106. This indicates that variansi on a variable performance practice undertaken by the company PT Efrata Retailindo of 10.6% can be explained by work stress variables and accounting information systems, while the remaining 89.4% explained by other factors outside the researched.

Pengaruh desain produk dan harga terhadap minat beli konsumen mebel jati jepara pada Toko Usaha Baru Furniture di Lubuk Alung

2019 ◽  
Vol 8 (2) ◽  
Author(s):  
Sutiyem Sutiyem ◽  
Thesa Alif Ravelby ◽  
Dessy Trismiyanti
Keyword(s):  
Product Design ◽  
Significant Influence ◽  
Design Variable ◽  
Quantitative Research ◽  
Coefficient Of Determination ◽  
Purchase Decision ◽  
Significant Positive Effect ◽  
Consumer Interest ◽  
Spss Software ◽  
Positive Effect

This study aims to determine the effect of product design and price on consumer interest in buying Jepara Teak furniture at the New Furniture Business Shop in Lubuk Alung. This type of research is associative quantitative research, the number of research samples were 100 people. Data was collected in the form of questionnaires and using analyzed SPSS software ver.21.0 for Windows. The conclusions from this study is the product design variable (X1) has a significant positive effect on purchase decision in Jati Jepara furniture at the New Furniture Business Shop in Lubuk Alung, as evidenced by t value > t table (10,400> 1,660) and a significant influence between price variables ( X2) purchase decision with t value> t table (2,015> 1,660). There is a positive and significant influence between product design (X1) price (X2), on purchase decision of Jati Jepara furniture consumers with an F-value 156,644> F- table (3,09) means that it affects together. The coefficient of determination (R²) results obtained a coefficient of 0.764 or 76.4%, while 23.6% is influenced by other variables.Keywords: Product design; prices; purchase decision.

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