Journal articles: 'Latent variable path analysis'

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Coffman, Donna L., and Robert C. MacCallum. "Using Parcels to Convert Path Analysis Models Into Latent Variable Models." Multivariate Behavioral Research 40, no. 2 (April 2005): 235–59. http://dx.doi.org/10.1207/s15327906mbr4002_4.

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Barrett, Paul. "Latent Variable Models: An Introduction to Factor, Path, and Structural Analysis." Personality and Individual Differences 29, no. 5 (November 2000): 999–1000. http://dx.doi.org/10.1016/s0191-8869(99)00239-1.

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Wardrop, James L., and John C. Loehlin. "Latent Variable Models: An Introduction to Factor, Path, and Structural Analysis." Journal of Educational Statistics 12, no. 4 (1987): 410. http://dx.doi.org/10.2307/1165058.

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Kline, Rex B. "Latent variable path analysis in clinical research: A beginner's tour guide." Journal of Clinical Psychology 47, no. 4 (July 1991): 471–84. http://dx.doi.org/10.1002/1097-4679(199107)47:4<471::aid-jclp2270470402>3.0.co;2-o.

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Boomsma, Anne. "Book Review : Latent Variable Models: An Introduction to Factor, Path, and Structural Analysis." Applied Psychological Measurement 12, no. 2 (June 1988): 211–13. http://dx.doi.org/10.1177/014662168801200212.

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Devlieger, Ines, and Yves Rosseel. "Factor Score Path Analysis." Methodology 13, Supplement 1 (June 1, 2017): 31–38. http://dx.doi.org/10.1027/1614-2241/a000130.

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Abstract. Theoretical researchers consider Structural Equation Modeling (SEM) to be the preferred method to study the relationships among latent variables. However, SEM has the disadvantage of requiring a large sample size, especially if the model is complex. Furthermore, since SEM estimates all parameters simultaneously, one misspecification in the model may influence the whole model. For these reasons, applied researchers often use a two-step Factor Score Regression (FSR) approach. In the first step, factor scores are calculated for the latent variables, which are used to perform a linear regression in the second step. However, this method results in incorrect regression coefficients. Croon (2002) developed a method that corrects for this bias. We combine this method of Croon (2002) with path analysis, resulting in Factor Score Path Analysis. This method results in correct path coefficients and has some advantages over SEM: it requires smaller sample sizes, can handle more complex models and the method is less sensitive to misspecifications, because of its stepwise nature. In conclusion, this method can be a suitable alternative for SEM, when one is dealing with a complex model and small sample sizes.

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Febriandani, Hasna, Abdul Muhaimin, and Dwi Andriani. "The Analysis of Purchase Intention of Processed Apple Products in Shopee." HABITAT 32, no. 3 (December 1, 2021): 173–83. http://dx.doi.org/10.21776/ub.habitat.2021.032.3.19.

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During the current pandemic, almost everything we need, both primary and secondary, we can fulfill from online services. In the era of globalization and the ease of online shopping transactions can lead to consumptive behavior, especially considering the current situation in the corona virus crisis, where consumer behavior has begun to change drastically. This study used Structural Equation Modeling-Partial Least Square (SEM-PLS) analysis with the WarpPLS approach, to predict the magnitude of the relationship among latent variables and between latent variable and its indicator. The dominant variables in the research on the effect of purchase intention of processed apple products at Shopee are trust, online shopping attitudes, subjective norms and purchase intentions. Trust in product purchase intention produces a path coefficient of 0.320 with a confidence interval value [0.160;0.481]. The test results showed that the path coefficient was positive with a high significance level. Online shopping attitude on product purchase intention produces a path coefficient of 0.422 with a confidence interval value [0.261; 0.627], the path coefficient was positive with a high significance level so that this sub hypothesis can be accepted. Subjective norm on product purchase intention produces a path coefficient of 0.250 with a confidence interval value [0.104;0.397], the path coefficient was positive with a high significance level. Purchase intention on purchasing decisions produces a path coefficient of 0.509 with a confidence interval value [0.370; 0.648], the path coefficient was positive with a high significance level.

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Tanaka, Akihiro, and Kuninori Nakamura. "Auditory Memory and Proficiency of Second Language Speaking: A Latent Variable Analysis Approach." Psychological Reports 95, no. 3 (December 2004): 723–34. http://dx.doi.org/10.2466/pr0.95.3.723-734.

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Previous studies of second language aptitude have mainly used verbal stimuli in memory tasks. Memory for musical stimuli has not been used in aptitude studies although music and language have structural similarity. In this study, 30 Japanese university students who speak English as a second language (19 men, M = 21.3 yr., SD = 1.8) participated in the experiment as volunteers. They performed verbal memory tasks, musical memory tasks, and English pronunciation tasks. Factor analysis indicated that verbal and musical memory abilities are better represented as a unitary factor rather than two independent factors. Further, a path analysis supported the hypothesis that the memory for both verbal and musical tasks affects proficiency of second language pronunciation, including prosodic features such as stress in word or intonation through a couple of sentences. The memory factor was interpreted as reflecting the performance of “auditory working memory.”

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Eshima, Nobuoki, Chooichiro Asano, and Minoru Tabata. "A developmental path model and causal analysis of latent dichotomous variables." British Journal of Mathematical and Statistical Psychology 49, no. 1 (May 1996): 43–56. http://dx.doi.org/10.1111/j.2044-8317.1996.tb01074.x.

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McDONALD, RODERICK P. "The Bilevel Reticular Action Model for Path Analysis with Latent Variables." Sociological Methods & Research 22, no. 3 (February 1994): 399–413. http://dx.doi.org/10.1177/0049124194022003007.

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Chaitawittanun, Nonthacha, Duangduen Bhanthumnavin, Duchduen Emma Bhanthumnavin, Kosol Meekun, Narisara Peungposop, and Saran Pimthong. "Psycho-Situational Path Model of Ambidextrous Preparation for Quality Aging in College Students." International Journal for Innovation Education and Research 8, no. 8 (August 1, 2020): 841–52. http://dx.doi.org/10.31686/ijier.vol8.iss8.2592.

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During the period of old age, everyone wishes to have good quality of living. However, only the ones who have been well-prepared at the younger age could make this wish comes true. This study aims at investigating the psychosocial antecedents of the preparation of quality aging based on ambidextrous approach. Samples were 489 undergraduate students. Path analysis with latent model revealed a good fit. The findings revealed that psychological latent trait (future orientation and self-control, need for achievement, mental health, and core self-evaluation) and situational latent variable (perceived modeling, social support, and social norm) directly affected the preparation for quality aging (present quality of life, knowledge acquisition, and knowledge usage) via the psychological latent state R2 of 0.606 latent (attitude towards preparation, and locus of control of preparation) with the. Discussion and implications are offered.

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Dewanto, Rizky Fajar. "Pengaruh Digitalisasi dan Citra Destinasi Pariwisata Terhadap Tingkat Kepuasan Pengunjung di Malang." Jurnal Ilmu Ekonomi JIE 6, no. 4 (November 30, 2022): 537–52. http://dx.doi.org/10.22219/jie.v6i4.22278.

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The purpose of this study was to analyze the effect of digitization and destination image on visitor satisfaction in Malang. The research method used is SmartPLS. PLS is used to confirm the theory and explain whether there is a relationship between latent variables, besides calculating the moderator variables directly. PLS can be used even if the data distribution is very skewed or not normally distributed because it uses a bootstrapping method and can be used for research with small samples. The results of the study based on the SmartPLS analysis tool found that the digitization and image of the destination played an important role in the development of the tourism sektor. The results of the analysis of the Path Coeffecient show that the digitization and destination image variables have a positive effect on the visitor satisfaction variable. Tujuan dari penelitian ini adalah untuk menganalisis pengaruh digitalisasi dan citra destinasi terhadap kepuasan pengunjung di Kota Malang. Metode penelitian yang digunakan adalah SmartPLS. PLS digunakan untuk mengkonfirmasi teori dan menjelaskan apakah ada hubungan antara variabel laten, selain menghitung variabel moderator secara langsung. PLS dapat digunakan walaupun sebaran data sangat miring atau tidak berdistribusi normal karena menggunakan metode bootstrap dan dapat digunakan untuk penelitian dengan sampel yang kecil. Hasil kajian berdasarkan alat analisis SmartPLS menemukan bahwa digitalisasi dan citra destinasi berperan penting dalam pengembangan sektor pariwisata. Hasil analisis Path Coeffecient menunjukkan bahwa variabel digitalisasi dan citra destinasi berpengaruh positif terhadap variabel kepuasan pengunjung.

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Singh, Kusum. "Book Review: Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis (4th ed.)." Applied Psychological Measurement 30, no. 3 (May 2006): 256–58. http://dx.doi.org/10.1177/0146621605280602.

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Kusuma, Wirajaya, Rifani Nur Sindy Setiawan, Kirti Verma, and Carina Firstca Utomo. "Structural Equation Modeling-Partial Least Square for Poverty Modeling in Papua Province." Jurnal Varian 4, no. 2 (April 30, 2021): 79–90. http://dx.doi.org/10.30812/varian.v4i2.852.

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Poverty in Papua Province in 2018 has increased from the previous year. The poverty rate in Papua Province in March 2018 reached 27,74%. This study aims to analyze the factors that influence it so that it can be handled properly. The research method used in this research is Structural Equation Modeling (SEM) with the Partial Least Squares (PLS) approach. The research variables used consisted of 4 latent variables (Poverty, Economy, Human Resources (HR), and Health) with 16 indicators (manifest variables). Based on the analysis that has been done, it is found that economic and health variables have a negative and significant effect on poverty with path coefficients of -0,421 and -0,270, respectively. The health variable has a positive and significant effect on HR with a path coefficient of 0,496. Meanwhile, the HR variable has a positive and significant effect on the economy with a path coefficient of 0,801. It can be concluded that there are two variables that have a significant effect on poverty in Papua Province, including the economy and health.

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Wahyuni, Rezi, Budi Susetyo, and Anwar Fitrianto. "HUBUNGAN AKREDITASI DAN UJIAN NASIONAL PADA SEKOLAH NEGERI DENGAN GENERALIZED STRUCTURED COMPONENT ANALYSIS." Indonesian Journal of Statistics and Its Applications 3, no. 3 (October 31, 2019): 260–71. http://dx.doi.org/10.29244/ijsa.v3i3.342.

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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.

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Zhang, Li Tian. "Analysis of Elastic Modulus Algorithm for Path Optimization Based on Latent Variables." Applied Mechanics and Materials 608-609 (October 2014): 196–200. http://dx.doi.org/10.4028/www.scientific.net/amm.608-609.196.

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According to the basic of education thought as a guide, compared with the implementation characteristics of traditional education, the network education is the new education model of contemporary science technology, to establishing the education evaluation model, and then the traditional education under the new situation carries out the SWOT analysis, it can be concluded that the emergence and existence of these two educational models are reasonable, the network education is the rational allocation for the resources of traditional education, it has also a great effect for the gradual improvement of education efficiency. At the same time, the network education should also learn from the traditional education’s success, two is the mutual competition, mutual promotion and mutual development.

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Stimson, James A. "The Dyad Ratios Algorithm for Estimating Latent Public Opinion." Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique 137-138, no. 1 (January 2018): 201–18. http://dx.doi.org/10.1177/0759106318761614.

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In the study of longitudinal movements in public opinion it is usually the case that data are abundant, but irregular. Both cases (times) and variables are numerous, but it is never the case that all cases are available for any one variable. The dyad ratios algorithm was created to make dimensional analysis possible for this perverse data structure. The central logic of the dyad ratios algorithm is explained. Central focus is on the use of ratios as a starting point, the recursive estimation procedure, validity estimation by iterative procedure and the bootstrapping of standard errors. The ability of the algorithm to estimate a known longitudinal path is tested with artificial data. Then dyad ratios is compared to principal components analysis for a particular real data problem where both are possible. A final section makes a limited comparison between dyad ratios and item response theory.

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Chen, Wenhui, and Yalin Lei. "Analysis of the impact path on factors of China’s energy-related CO2 emissions: a path analysis with latent variables." Environmental Science and Pollution Research 24, no. 6 (January 3, 2017): 5757–72. http://dx.doi.org/10.1007/s11356-016-8300-y.

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Kock, Ned. "How Likely is Simpson's Paradox in Path Models?" International Journal of e-Collaboration 11, no. 1 (January 2015): 1–7. http://dx.doi.org/10.4018/ijec.2015010101.

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Simpson's paradox is a phenomenon arising from multivariate statistical analyses that often leads to paradoxical conclusions in the field of e-collaboration as well as many other fields where multivariate methods are employed. This work derives a general inequality for the occurrence of Simpson's paradox in path models with or without latent variables. The inequality is then used to estimate the probability that Simpson's paradox would occur at random in path models with two predictors and one criterion variable. This probability is found to be approximately 12.8 percent, slightly higher than 1 occurrence per 8 path models. This estimate suggests that Simpson's paradox is likely to occur in empirical studies, in the field of e-collaboration and other fields, frequently enough to be a source of concern.

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Lohmoller, Jan-Bernd. "The PLS Program System: Latent Variables Path Analysis with Partial Least Squares Estimation." Multivariate Behavioral Research 23, no. 1 (January 1988): 125–27. http://dx.doi.org/10.1207/s15327906mbr2301_7.

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Violato, Claudio, Emilio Mauro Violato, and Efrem Mauro Violato. "Impact of the stringency of lockdown measures on covid-19: A theoretical model of a pandemic." PLOS ONE 16, no. 10 (October 5, 2021): e0258205. http://dx.doi.org/10.1371/journal.pone.0258205.

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Background How effective have lockdowns been at reducing the covid-19 infection and mortality rates? Lockdowns influence contact among persons within or between populations including restricting travel, closing schools, prohibiting public gatherings, requiring workplace closures, all designed to slow the contagion of the virus. The purpose of the present study was to assess the impact of lockdown measures on the spread of covid-19 and test a theoretical model of the covid-19 pandemic employing structural equation modelling. Methods Lockdown variables, population demographics, mortality rates, infection rates, and health were obtained for eight countries: Austria, Belgium, France, Germany, Italy, Netherlands, Spain, and the United Kingdom. The dataset, owid-covid-data.csv, was downloaded on 06/01/2020 from: https://github.com/owid/covid-19-data/tree/master/public/data. Infection spread and mortality data were depicted as logistic growth and analyzed with stepwise multiple regression. The overall structure of the covid-19 data was explored through factor analyses leading to a theoretical model that was tested using latent variable path analysis. Results Multiple regression indicated that the time from lockdown had a small but significant effect (β = 0.112, p< 0.01) on reducing the number of cases per million. The stringency index produced the most important effect for mortality and infection rates (β = 0.588,β = 0.702, β = 0.518, β = 0.681; p< 0.01). Exploratory and confirmatory analyses resulted in meaningful and cohesive latent variables: 1) Mortality, 2) Infection Spread, 3) Pop Health Risk, and 4) Health Vulnerability (Comparative Fit Index = 0.91; Standardized Root Mean Square Residual = 0.08). Discussion The stringency index had a large impact on the growth of covid-19 infection and mortality rates as did percentage of population aged over 65, median age, per capita GDP, diabetes prevalence, cardiovascular death rates, and ICU hospital beds per 100K. The overall Latent Variable Path Analysis is theoretically meaningful and coherent with acceptable fit indices as a model of the covid-19 pandemic.

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Kuo, Yen-Ku, Tsung-Hsien Kuo, Jiun-Hao Wang, and Li-An Ho. "The Antecedents of University Students’ E-Learning Outcome under the COVID-19 Pandemic: Multiple Mediation Structural Path Comparison." Sustainability 14, no. 24 (December 14, 2022): 16794. http://dx.doi.org/10.3390/su142416794.

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The COVID-19 pandemic in late 2019 has severely affected the education sector. In order to avoid clustering, higher education has begun to implement a large number of e-learning courses. Although modern technologies are relatively mature, learning outcomes do not entirely depend on advanced technologies. The purpose of this study is to explore how self-directed learning and the information literacy of university students affect their e-learning attitude, and to understand the variables that mediate their effects on the learning effectiveness. This is a survey research and a survey questionnaire was used to collect data. A total of 714 valid samples were retrieved. A confirmatory factor analysis was used to determine the reliability and validity of each variable, and the latent variable modeling was utilized to test the research hypotheses. The results showed that self-directed learning and information literacy had a significant positive impact on e-learning attitudes and learning effectiveness, and e-learning attitudes had a significant positive influence on the learning effectiveness. Through the structural model verification analysis, it was found that e-learning attitudes are the main intermediary mechanism among all of the variables. By comparing multiple intermediary variables, it was found that self-directed learning, as an independent variable, exerted indirect effects on the learning effectiveness through e-learning.

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Kinney, Adam, Ryan O. Stephenson, Alison M. Cogan, Jeri E. Forster, Holly R. Gerber, and Lisa A. Brenner. "Participation Mediates the Relationship Between Postconcussive Symptoms and Suicidal Ideation Among Veterans." American Journal of Occupational Therapy 76, Supplement_1 (July 1, 2022): 7610505007p1. http://dx.doi.org/10.5014/ajot.2022.76s1-rp7.

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Abstract Date Presented 04/01/2022 We present results of a latent variable path analysis indicating that postconcussive symptoms may heighten risk for suicidal thoughts among Veterans by limiting successful participation. We discuss implications of results with respect to OT’s role in suicide prevention efforts. Primary Author and Speaker: Adam Kinney Contributing Authors: Ryan O. Stephenson, Alison M. Cogan, Jeri E. Forster, Holly R. Gerber, Lisa A. Brenner

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Khairi, M. Ihsan, Dwi Susanti, and Sukono Sukono. "Study on Structural Equation Modeling for Analyzing Data." International Journal of Ethno-Sciences and Education Research 1, no. 3 (July 6, 2021): 52–60. http://dx.doi.org/10.46336/ijeer.v1i3.295.

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Structural Equation Model (SEM) is a combination of two separate statistical methods, namely factor analysis developed in psychology and psychometry and simultaneous equation model developed in econometrics. Factor analysis was first introduced by Galton in 1869 and Pearson (Pearson and Lee, 1904). Spearman's (1904) research is the development of a general factor analysis model in his research relating to the structure of mental abilities, Spearman stated that the intercorrelation test between mental abilities can determine general ability factors and special ability factors. SEM is a combination of factor analysis and path analysis into one comprehensive statistical method. Path analysis itself is the forerunner of the structural equation of Sewwl Wright's research in the field of biometrics. Wright's contribution is to be able to show that the correlation between variables is related to the parameters of a model described by a path (path diagram). In SEM there are 2 variables, namely latent variables (exogenous and endogenous) and indicator variables. SEM has 2 equation models, namely the measurement equation model and the structural equation model. SEM also has 2 errors, namely the error for the measurement equation model and the error for the structural equation model. In general, SEM is formed from the relationship between latent variables and their respective indicator variables. To test whether the existing indicator variables are valid indicators for measuring the latent construct, Confirmatory Factor Analysis (CFA) is used. Data analysis with SEM must meet the existing SEM assumptions. The model feasibility test is carried out based on the goodness of fit criteria. The stages in SEM analysis are theoretical model development, flow chart drawing, flow chart conversion into equation form, input matrix and model parameter estimation techniques, model problem identification, evacuating model parameter estimates, model interpretation and model modification.

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Donni, Ravichandra, Omkar Dastane, Herman Fassou Haba, and Karthik Selvaraj. "Consumer Perception Factors for Fashion M-Commerce and its Impact on Loyalty among Working Adults." Business and Economic Research 8, no. 2 (April 23, 2018): 168. http://dx.doi.org/10.5296/ber.v8i2.13044.

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The purpose of this study was to investigate the influence of selected customer perceived value factors on the consumer loyalty towards Mobile commerce in Malaysia towards fashion and apparel industry. This research mainly proposes on the integrated model of dependent variable loyalty of consumer behavior with six independent variables such as Efficiency, System availability, Fulfillment, price as perceived value elements. Explanatory research is adopted and data was collected using a questionnaire developed based on the past researches. The sample of 215 M-shoppers is collected using convenience sampling and then analyzed with help of AMOS 22 tool mainly verified normality, reliability, confirmatory factor analysis, structural equation modelling and path analysis. Correlation Analysis has been carried out for the latent constructs of the SEM to find the strength of relationship between variables and through the Path Analysis R-square value obtained indicated that the model explains most of the variability of the response data around its mean. Then, significance of the SEM is obtained using the P-value in which the exogenous variables ‘Efficiency & Privacy’ are found to be significant with the ‘Perceived Value’ and one of the exogenous variable ‘Price’ is found to be significant directly with the endogenous variable ‘Loyalty’. Mediating effects were considered to find the direct effects of exogenous variables on endogenous variables. Efficiency, privacy and price are the three important factors that any fashion industry in M-commerce should consider before marketing its products through mobile applications. Thus, businesses developing M-Commerce can come out with suitable value proposition for their M-shoppers based on the findings of this research.

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Shengjin, Wang, and Chen Ying. "Influencing Factors Analysis of China Metropolis Online Business Based on SEM." E3S Web of Conferences 236 (2021): 05005. http://dx.doi.org/10.1051/e3sconf/202123605005.

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This study aims at identifying the factors that affect the development of online business of China’s metropolis from the perspective of innovation diffusion theory. Firstly, nine hypotheses that may have influence on the development of web business are extracted according to the theory of innovation diffusion based on the related foreign and domestic literatures’ review, and a structural equation of the affecting factors is constructed. Data is gathered by questionnaires and sample survey then. Reliability test of observed variables is processed by SPSS, and AMOS verifies the overall fitting goodness of the model. Moreover, factors with affecting path and coefficient of the latent variable are calculated out. Studies have shown that five factors, including changing risk of business model, convenience of the system using, degree of competition from the same industry, pressure from partners and the support from corporate chief executives affect the development of online business strongly. These conclusions provide a basis for decision-making in development of China's online business.

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Kim, Yejin, Seulah Lee, Yeongdae Cho, and Minsoo Kim. "Analysis of Causal Relationships for Nutrient Removal of Activated Sludge Process Based on Structural Equation Modeling Approaches." Applied Sciences 9, no. 7 (April 3, 2019): 1398. http://dx.doi.org/10.3390/app9071398.

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The removal process of activated sludge in sewage treatment plants is very nonlinear, and removal performance has a complex causal relationship depending on environmental factors, influent load, and operating factors. In this study, how causal relationships are expressed in collected data was identified by structural equation modeling. First, path modeling was attempted as a preliminary step in structural equation model (SEM) construction and, as a result, the nutrient-removal mechanism could not be sufficiently represented as a direct causal relationship between measured variables. However, as a result of the deduced SEMs for effluent total nitrogen (T-N) and total phosphorus (T–P) concentrations, accompanied by exploratory factor analysis to extract latent variables, a causal network was formed that describes the direct or indirect effect of the latent factors and measured variables. Hereby, this study suggests that it is possible to construct an SEM explaining the nutrient-removal mechanism of the activated-sludge process with latent variables. Moreover, nonlinear features embedded in the mechanism could be represented by SEM, which is a model based on linearity, by including causal relations and variables that were not derived by path analysis. This attempt to model the direct and indirect causalities of the process could enhance the understanding of the process, and help decision making such as changing the driving conditions that would be required.

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Hu, Shenping, Zhuang Li, Yongtao Xi, Xunyu Gu, and Xinxin Zhang. "Path Analysis of Causal Factors Influencing Marine Traffic Accident via Structural Equation Numerical Modeling." Journal of Marine Science and Engineering 7, no. 4 (April 4, 2019): 96. http://dx.doi.org/10.3390/jmse7040096.

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Many causal factors to marine traffic accidents (MTAs) influence each other and have associated effects. It is necessary to quantify the correlation path mode of these factors to improve accident prevention measures and their effects. In the application of human factors to accident mechanisms, the complex structural chains on causes to MTA systems were analyzed by combining the human failure analysis and classification system (HFACS) with theoretical structural equation modeling (SEM). First, the accident causation model was established as a human error analysis classification in sight of a MTA, and the constituent elements of the causes of the accident were conducted. Second, a hypothetical model of human factors classification was proposed by applying the practice of the structural model. Third, with the data resources from ship accident cases, this hypothetical model was discussed and simulated, and as a result, the relationship path dependency mode between the latent independent variable of the accident was quantitatively analyzed based on the observed dependent variable of human behavior. Application examples show that relationships in the HFACS are verified and in line with the path developing mode, and resource management factors have a pronounced influence and a strong relevance to the causal chain of the accidents. Appropriate algorithms for the theoretical model can be used to numerically understand the safety performance of marine traffic systems under different parameters through mathematical analysis. Hierarchical assumptions in the HFACS model are quantitatively verified.

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Druică, Elena, Călin Vâlsan, Rodica Ianole-Călin, Răzvan Mihail-Papuc, and Irena Munteanu. "Exploring the Link between Academic Dishonesty and Economic Delinquency: A Partial Least Squares Path Modeling Approach." Mathematics 7, no. 12 (December 15, 2019): 1241. http://dx.doi.org/10.3390/math7121241.

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This paper advances the study of the relationship between the attitude towards academic dishonesty and other types of dishonest and even fraudulent behavior, such as tax evasion and piracy. It proposes a model in which the attitudes towards two types of cheating and fraud are systematically analyzed in connection with a complex set of latent construct determinants and control variables. It attempts to predict the tolerance towards tax evasion and social insurance fraud and piracy, using academic cheating as the main predictor. The proposed model surveys 504 student respondents, uses a partial least squares—path modeling analysis, and employs two subsets of latent constructs to account for context and disposition. The relationship between the outcome variable and the subset of predictors that account for context is mediated by yet another latent construct—Preoccupation about Money—that has been shown to strongly influence people’s attitude towards a whole range of social and economic behaviors. The results show academic dishonesty is a statistically significant predictor of an entire range of unethical and fraudulent behavior acceptance, and confirm the role played by both contextual and dispositional variables; moreover, they show that dispositional and contextual variables tend to be segregated according to how they impact the outcome. They also show that money priming does not act as a mediator, in spite of its stand-alone impact on the outcome variables. The most important result, however, is that the effect size of the main predictor is large. The contribution of this paper is two-fold: it advances a line of research previously sidestepped, and it proposes a comprehensive and robust model with a view to establish a hierarchy of significance and effect size in predicting deviance and fraud. Most of all, this research highlights the central role played by academic dishonesty in predicting the acceptance of any type of dishonest behavior, be it in the workplace, at home, or when discharging one’s responsibilities as a citizen. The results presented here give important clues as to where to start intervening in order to discourage the acceptance of deviance and fraud. Educators, university professors, and academic administrators should be at the forefront of targeted campaigns and policies aimed at fighting and reducing academic dishonesty.

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Lee, Nanhee, Hyojeong Jeon, and Eunkyoung Goh. "Path Analysis of Youth Betting Behavior by Accessibility Level." Korean Association For Learner-Centered Curriculum And Instruction 22, no. 15 (August 15, 2022): 151–66. http://dx.doi.org/10.22251/jlcci.2022.22.15.151.

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Objectives The purpose of this study is to provide data for an integrated understanding of youth betting behaviors and customized interventions for each path by identifying the paths of youth betting behaviors by accessibility level. Methods For this purpose, data from 571 adolescents residing across the country were collected, descriptive statistics and correlation analysis were performed with SPSS 21.0, and latent profile analysis was performed using the ‘tidyLPA’ package in R version 3.6.1 environment. Next, the pathways of neglect and abuse on depression, impulsivity, betting behavior expectations, irrational beliefs, and adolescent betting behaviors were identified with AMOS 21.0 by level of betting behavior accessibility. Results First, for adolescent betting behavior paths by accessibility level, the coefficient differences between the path from impulsivity to betting behavior, the path from betting behavior expectation to betting behavior, and the path from irrational belief to betting behavior were found to be statistically significant. Second, the path that affects betting behavior in the group with high accessibility is the path from neglect to betting behavior through irrational beliefs, the path from neglect to depression, impulsivity, betting behavior expectations, the path to betting behavior through irrational beliefs, and the path from abuse to betting behavior The path to betting behavior through depression, impulsivity, betting behavior expectation, and irrational beliefs and the path from abuse to betting behavior through impulsivity, betting behavior expectation and irrational beliefs are significant. Third, in the group with low accessibility, a significant path leading to betting behavior does not appear. Conclusions This study confirmed the distinct differences in specific pathways on adolescent betting behavior by accessibility level, and confirmed multidimensional pathways by accessibility level by inputting betting behavior expectancy variables, which were not covered in domestic studies, together with major variables of adolescent betting behaviors. This broadened the understanding of youth betting behavior and presented evidence for customized intervention.

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Sasaki, Daisuke, Kana Moriyama, and Yuichi Ono. "Hidden Common Factors in Disaster Loss Statistics: A Case Study Analyzing the Data of Nepal." Journal of Disaster Research 13, no. 6 (November 1, 2018): 1032–38. http://dx.doi.org/10.20965/jdr.2018.p1032.

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This study aims to examine common hidden factors in disaster loss statistics and identify clues for verifying the fitness of the global targets of the Sendai Framework for Disaster Risk Reduction 2015–2030 (SFDRR) to rule countries’ effort in reducing disaster risks. In this study, we first conducted an exploratory factor analysis (EFA), followed by a confirmatory factor analysis (CFA) using structural equation modeling (SEM). As a result of the EFA, we were able to extract three factors, namely Housing, Casualties or Education, and Relocation. In the analysis of SEM, we assumed three latent variables based on the results of the EFA. The relationship between the latent and observed variables was established in a manner that conformed to the implications of the EFA. According to the SEM results, we eventually identified three latent variables, namely Housing, Education and Relocation, as hidden common factors. Based on this identification, our judgment indicates that the latent variables appeared to be related to the following global targets of SFDRR: (b) those concerning the number of affected people and (d) those concerning damages to infrastructure and disruptions to basic services. It was found that relationships between variables could be clearly illustrated by using the path diagram. This study can be considered as a good example of introducing SEM to visualize hidden common factors and their relationships in an intelligible manner. Based on the results, we propose a starting point for discussing the fitness of SFDRR’s global targets by utilizing EFA and CFA (SEM) techniques. The path diagram can indicate the extent to which the indicators contribute to global targets that will be represented as latent variables. In the end, explicit reference should be made to the material data’s limitations in the disaster loss statistics. An effort to elaborate the input data themselves must be made in the near future.

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Jang, Peter, Kwanghee Jung, and Mario Beruvides. "Application of IRT Models to Selection of Bidding Paths in Financial Transmission Rights Auction: U.S. New England." Energies 13, no. 13 (June 30, 2020): 3325. http://dx.doi.org/10.3390/en13133325.

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This paper explores a way to apply Item Response Theory (IRT), one of the popular statistical methodologies in measurement and psychometrics, to evaluate Financial Transmission Rights (FTR) paths in the U.S. electricity market. FTR is an energy derivative product to hedge congestion cost risks inherent in constrained transmission lines. In New England, with about 1200 pricing locations, the theoretical combinations of FTR paths amount to 1.4 million in prevailing flows alone. With capital constraints, it is imperative that FTR market participants build the capability to evaluate FTR paths to bid on. IRT provides a framework of how well tests work, and how individual items work on tests, estimating respondents’ latent abilities, and individual item parameters. IRT is utilized to analyze historical electricity data of 2019 for a daily congestion cost of eight customer load zones and one hub in the U.S., New England, for the evaluation of FTR paths. In the analysis, an item represents an FTR path, while item difficulty, item discrimination, and a latent trait variable for the path correspond to the path profitability, risk level, and daily congestion ability, respectively. This paper explores the experimental procedures by which IRT, a psychometric tool, may also be applicable in complex energy markets, providing a consistent and standardized analytical framework to address the issues of selection and prioritization among multiple opportunities. FTR path evaluation is conducted in three steps to determine bid priority paths in FTR auctions: parameter significance tests, ranking on path profitability and risk level, and weighting scores of individual rankings on the two criteria.

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Ledimo, Ophillia, and Nico Martins. "Validation of an employee satisfaction model: A structural equation model approach." Journal of Governance and Regulation 4, no. 1 (2015): 78–87. http://dx.doi.org/10.22495/jgr_v4_i4_p8.

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The purpose of this study was to validate an employee satisfaction model and to determine the relationships between the different dimensions of the concept, using the structural equation modelling approach (SEM). A cross-sectional quantitative survey design was used to collect data from a random sample of (n=759) permanent employees of a parastatal organisation. Data was collected using the Employee Satisfaction Survey (ESS) to measure employee satisfaction dimensions. Following the steps of SEM analysis, the three domains and latent variables of employee satisfaction were specified as organisational strategy, policies and procedures, and outcomes. Confirmatory factor analysis of the latent variables was conducted, and the path coefficients of the latent variables of the employee satisfaction model indicated a satisfactory fit for all these variables. The goodness-of-fit measure of the model indicated both absolute and incremental goodness-of-fit; confirming the relationships between the latent and manifest variables. It also indicated that the latent variables, organisational strategy, policies and procedures, and outcomes, are the main indicators of employee satisfaction. This study adds to the knowledge base on employee satisfaction and makes recommendations for future research.

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Kock, Ned. "Hypothesis Testing with Confidence Intervals and P Values in PLS-SEM." International Journal of e-Collaboration 12, no. 3 (July 2016): 1–6. http://dx.doi.org/10.4018/ijec.2016070101.

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E-collaboration researchers usually employ P values for hypothesis testing, a common practice in a variety of other fields. This is also customary in many methodological contexts, such as analyses of path models with or without latent variables, as well as simpler tests that can be seen as special cases of these (e.g., comparisons of means). The author discusses here how a researcher can use another major approach for hypothesis testing, the one building on confidence intervals, in analyses of path models with latent variables employing partial least squares structural equation modeling (PLS-SEM). The author contrasts this approach with the one employing P values through the analysis of a simulated dataset, created based on a model grounded on past theory and empirical research. The model refers to social networking site use at work and its impact on job performance. The results of the analyses suggest that tests employing confidence intervals and P values are likely to lead to very similar outcomes in terms of acceptance or rejection of hypotheses.

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Asyifa, Rahma Dany, Agus M. Soleh, and Bagus Sartono. "Evaluasi Faktor yang Memengaruhi Usability Aplikasi Thymun Menggunakan Structural Equation Model-Partial Least Square." Xplore: Journal of Statistics 10, no. 3 (September 30, 2021): 214–25. http://dx.doi.org/10.29244/xplore.v10i3.743.

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Application development must be done by considering the usability factor of the application. Three aspects of usability measurement, namely usefulness, satisfaction, and ease of use, are latent variables that cannot be measured directly, so the appropriate analysis is the Structural Equation Model-Partial Least Square (SEM-PLS). PLS is a SEM analysis approach that does not require assumptions of data distribution and a minimum number of observations. The measurement of the usability of the Thymun application is described in two SEM-PLS models. This study aims to determine the best model and determine the effect of usefulness, satisfaction, and ease of use on the usability of the Thymun application. The data used is survey data to 44 Thymun application users. The sampling technique used was purposive sampling. The results showed that the best model has a good measure with an R-square value of 0.730 and Q2 0.453 with a Goodness of Fit 0.736. The variables of usefulness and ease of use have a significant effect on the 5% real level with path coefficient values of 0.255 and 0.636. While the satisfaction variable does not have a significant effect on the 5% real level with a path coefficient of 0.058. Thymun application usability score is 76.47.

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van Riper, Carena J., and Gerard T. Kyle. "Understanding the internal processes of behavioral engagement in a national park: A latent variable path analysis of the value-belief-norm theory." Journal of Environmental Psychology 38 (June 2014): 288–97. http://dx.doi.org/10.1016/j.jenvp.2014.03.002.

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Shin, Yunbeom, and Hyoheon Won. "Relationship between learner-centered classes and academic achievement of high school students: Focusing on the longitudinal mediating effect of school happiness." Korean Society for Educational Evaluation 35, no. 4 (December 31, 2022): 609–31. http://dx.doi.org/10.31158/jeev.2022.35.4.609.

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In order to analyze the longitudinal effect of learner-centered classes of general high school students on academic achievement through school happiness, this study conducted a univariate and multivariate latent growth model analysis using data of 1,833 general high school students in the 4th and 6th years of the BELS. First, looking at the development trajectory of each research variable, it was confirmed that the average and rate of change of all variables were statistically significant, and there was a difference between individuals in changes according to grades, and students with high initial values were likely to have a relatively high rate of change. However, as the grade went up, learner-centered classes and school happiness decreased, but there was a difference in academic achievement. Next, as a result of verifying the influence of each path of the multivariate latent growth model, statistically significant influence of all paths was confirmed, but there was a difference in static and negative influence. Finally, as a result of analyzing the longitudinal mediating effect of school happiness in the relationship between learner-centered class and academic achievement, statistically significant partial mediating effect was verified in each path of initial value and rate of change. In particular, the initial value of learner-centered classes was found to have a statistically significant negative effect on the initial value of academic achievement, but statistically significant static mediating paths were analyzed when school happiness was used as a parameter.

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Xu, Xin. "Analysis of Influencing Factors of Teaching Effect Based on Structural Equation Model." Complexity 2021 (March 4, 2021): 1–10. http://dx.doi.org/10.1155/2021/6618445.

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Structural equation model is a multivariate statistical analysis method. It can not only test some unpredictable abstract ideas, but also design parameters for the causal connection model between independent variables and dependent variables. Among them, the analysis of various latent variables is based on the verification factor analysis technology. The research first collects various relevant data, derives the latent variables and measurement variables, then composes the measurement model, and then verifies the adaptability of the measurement model structure mode through actual data collection. When such suitable factors are determined, a causal model based on path analysis technology for latent variables, that is, a structural model, can be used for parameter design. This article uses the structural equation model as an analysis tool, starting from the three aspects of teachers, cases, and students to evaluate the application effect of the case teaching method in the classroom teaching of intellectual property law course and construct a structural equation model of the influencing factors of the case teaching effect. To understand students’ satisfaction with case teaching effects and related influencing factors, the research results show that the effect of case teaching is jointly affected by the level of teachers, case selection, and student response. Among them, teacher factors have the greatest impact on case teaching effects, followed by case factors, and students have the least.

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Ghofur, Abdul, and Puji Sucia Sukmaningrum. "PEGARUH GOOD CORPORATE GOVERNANCE TERHADAP EFISIENSI BANK SYARIAH TAHUN 2012-2016 DENGAN KINERJA SOSIAL SEBAGAI VARIABEL INTERVENING." Jurnal Ekonomi dan Bisnis Islam (Journal of Islamic Economics and Business) 4, no. 1 (November 2, 2018): 30. http://dx.doi.org/10.20473/jebis.v4i1.10047.

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This study aims to determine the effect of Good Corporate Governance and social performance on efficiency in Bank Syariah Period 2012-2016. The sample in this study used a purposive sampling method of Islamic Commercial Banks (BUS) in Indonesia, from 13 BUS took 6 BUS that met the sample criteria to be tested. Furthermore, this research uses path analysis, while the research approach used is quantitative approach using analysis technique PLS (Partial Least Square). In this research, there are three latent variables namely Good Corporate Governance as an exogenous or independent variable, social performance as endogen intervention variable, and efficiency as an endogen variable. The indicators used to reflect the Good Corporate Governance Variables are the Board of Commissioners (DK), the Composition of Independent Commissioners (KDKI), the Sharia Supervisory Board (DPS), the Frequency of Sharia Supervisory Board Meetings (FRDPS), and the Frequency of Audit Committee Meetings (FRKA). The indicators used to reflect social performance are financing Mudharabah-Musyarakah, Zakat, and Qard.. Furthermore, the efficiency indicator is reflected by the ratio of BOPO (Operational Cost to Operating Income).The results of this study indicate that GCG has a significant positive effect on efficiency, GCG has a significant positive effect on social performance, social performance has a significant negative effect on efficiency, GCG has a significant negative effect on efficiency through social performance. Keywords: Good Corporate Governance, Social Performance, Efficiency, Islamic Banks

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Williams, Larry J., Ernest H. O’Boyle, and Jia (Joya) Yu. "Condition 9 and 10 Tests of Model Confirmation: A Review of James, Mulaik, and Brett (1982) and Contemporary Alternatives." Organizational Research Methods 23, no. 1 (October 26, 2017): 6–29. http://dx.doi.org/10.1177/1094428117736137.

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Structural equation modeling (SEM) serves as one of the most important advances in the social sciences in the past 40 years. Through a combination of factor analysis and path analysis, SEM allows organizational researchers to test causal models while accounting for random and nonrandom (bias) measurement error. SEM is now one of the most commonly used analytic techniques and its modern day ubiquity can be traced in large part to a series of intellectual contributions by Larry James. The current article focuses on the seminal work, James, Mulaik, and Brett (1982), and the unique contribution of the “conditions” required for appropriate confirmatory inference with the path and latent variable models. We discuss the importance of James et al.’s Condition 9 and 10 tests, systematically review 14 years of studies using SEM in leading management journals and reanalyze results based on new techniques that extend James et al. (1982), and conclude with suggestions for improved Condition 9 and 10 assessments.

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Thunberg, Sarah M., Eugénie S. Euskirchen, John E. Walsh, and Kyle M. Redilla. "Diagnosis of Atmospheric Drivers of High-Latitude Evapotranspiration Using Structural Equation Modeling." Atmosphere 12, no. 10 (October 18, 2021): 1359. http://dx.doi.org/10.3390/atmos12101359.

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Evapotranspiration (ET) is a relevant component of the surface moisture budget and is associated with different drivers. The interrelated drivers cause variations at daily to interannual timescales. This study uses structural equation modeling to diagnose the drivers over an ensemble of 45 high-latitude sites, each of which provides at least several years of in situ measurements, including latent heat fluxes derived from eddy covariance flux towers. The sites are grouped by vegetation type (tundra, forest) and the presence or absence of permafrost to determine how the relative importance of different drivers depends on land surface characteristics. Factor analysis is used to quantify the common variance among the variables, while a path analysis procedure is used to assess the independent contributions of different variables. The variability of ET at forest sites generally shows a stronger dependence on relative humidity, while ET at tundra sites is more temperature-limited than moisture-limited. The path analysis shows that ET has a stronger direct correlation with solar radiation than with any other measured variable. Wind speed has the largest independent contribution to ET variability. The independent contribution of solar radiation is smaller because solar radiation also affects ET through various other drivers. The independent contribution of wind speed is especially apparent at forest wetland sites. For both tundra and forest vegetation, temperature loads higher on the first factor when permafrost is present, implying that ET will become less sensitive to temperature as permafrost thaws.

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Joo, Susanna, Seong Hee Kim, Changmin Lee, Kwang Joon Kim, DaeEun Kim, YoonMyung Kim, and Hey Jung Jun. "The Association Between Spousal Support And Attitude For Gerontechnology Via Facilitating Conditions." Innovation in Aging 5, Supplement_1 (December 1, 2021): 925. http://dx.doi.org/10.1093/geroni/igab046.3348.

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Abstract This study examined the mediating effects of facilitating conditions (FC) on the association between types of social support providers and attitude toward using gerontechnology (AUG) or between types of social support and AUG. The sample was 256 older Koreans having a partner and children (N=256; 66-88 years old; M=69.91; SD=4.19). The dependent variable was AUG in terms of an exoskeleton robot for exercise. There were two kinds of independent variables: 1) four types of social support provider (spouse, children, siblings/relatives, and friends/neighbors), and 2) four types of social support (emotional, instrumental, physical, and financial support). Mediating variable was calculated as the mean of FC from five questions. There were two analytic steps: 1) structural equation modeling with four latent variables about types of social support provider, and 2) path analysis with four types of social support if only for significant providers at the first analysis. The results from the first step of analysis showed that only social support from spouses had a significant effect on AUG via FC to use gerontechnology. In the second step of analysis, emotional support from spouses was associated with the higher level of AUG via FC to use gerontechnology. The findings could shed light on the salience of emotional support from spouses in terms of the positive attitude on technology usage in later life through enhancing FC for technology acceptance.

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Marques, Carlos Peixeira, and Ana Teresa Bernardo Guia. "Gender, knowledge and motivation for wine purchasing." International Journal of Wine Business Research 30, no. 4 (November 19, 2018): 481–92. http://dx.doi.org/10.1108/ijwbr-07-2017-0049.

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Purpose The purpose of this paper is to verify if the gender effects described in the wine consumer behaviour literature, namely, concerning information search and the motivations to buy, may be explained by the mediating effect of subjective knowledge, taking into consideration that the importance of knowledge in the decision process is gender specific. Design/methodology/approach A path analysis was modelled with an exogenous variable (gender), a mediating variable (subjective knowledge) and four dependent variables (need for information and three motivational dimensions). The model was assessed with empirical data obtained from a sample of 523 shoppers in large supermarkets in the areas of Lisbon and Oporto, Portugal. Structured interviews were conducted at checkout, collecting information on the relevant variables. Scales measuring the latent variables (knowledge, information and motivation) were previously validated through confirmatory factor analysis in a sample of 217 wine consumers. Findings Subjective knowledge fully mediates the effects of gender on motivation and information needs. Men think of themselves as more knowledgeable in wines and the mediation effect explains why, compared to women, they use less personal information sources and are more motivated to purchase wine. Practical implications The authors suggest promotion programmes in large supermarkets focussing on opportunities for wine knowledge development. Originality/value The study contributes to the literature by introducing and validating an alternative formulation of gender effects on wine shopping, emphasising the role of the purchaser’s perceived or subjective knowledge.

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Wicaksono, Fermi Dwi, Udisubakti Ciptomulyono, Ketut Buda Artana, and Mohammad Isa Irawan. "STATISTICAL ANALYSIS OF THE HIGH POTENTIAL INCIDENT IN ANDALS OIL OF INDONESIA." Jurnal Teknologi 83, no. 2 (February 2, 2021): 1–13. http://dx.doi.org/10.11113/jurnalteknologi.v83.14884.

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The oil and gas industry involves latent risks which are considered as one of the most severe consequences. This circumstance mainly due to the existence of intrinsic hazards involved. As part of process safety management, past incidents analysis should be performed to eliminate the potential of significant accident occurrence. It is crucial to identify the root cause of the incidents. This research discloses the degree of importance of causal factors in contributing to an incident. The methodology based on regression analysis and path analysis is performed to identify the degree of importance of incident causes. A case study is performed at Andals Oil of Indonesia to demonstrate the most significant factor leading to an incident. As the baseline for this research, incident data are gathered from Andals Oil's database during 2006 – 2018. The statistics describe the most frequent type of incident that occurs during the oil and gas field operations. Three major root causes in the oil and gas industry are evaluated: 1. Organizational system factor; 2. Job factor leading to unsafe working conditions; 3. Human-behavioral factor. Based on the regression analysis and path analysis, it is concluded that the number of High potential incidents is directly affected by Job factor leading to unsafe condition and Human-behavioral factor. Although the Organizational system factor may not significantly affect the number of High potential incidents, this factor still directly engenders unsafe working condition by affecting variable Job factors.

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Ciorba, Charles R., and Brian E. Russell. "A Proposed Model of Jazz Theory Knowledge Acquisition." Journal of Research in Music Education 62, no. 3 (September 12, 2014): 291–301. http://dx.doi.org/10.1177/0022429414542979.

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The purpose of this study was to test a hypothesized model that proposes a causal relationship between motivation and academic achievement on the acquisition of jazz theory knowledge. A reliability analysis of the latent variables ranged from .92 to .94. Confirmatory factor analyses of the motivation (standardized root mean square residual [SRMR] = .067) and jazz theory (SRMR = .063) measures indicated a good fit of the predicted model to the observed data. Results of the latent path model indicated good fit (χ2 = 20.08, p = .692, df = 24, N = 102) and large, positive, and statistically significant direct effects of motivation (β = 0.65) and academic achievement (β = 0.56) on jazz theory knowledge acquisition. The successful identification of this proposed model lends enough support for continued investigation into the process surrounding the acquisition of jazz theory knowledge.

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Yu, Rongjie, Yin Zheng, Mohamed Abdel-Aty, and Zhen Gao. "Exploring crash mechanisms with microscopic traffic flow variables: A hybrid approach with latent class logit and path analysis models." Accident Analysis & Prevention 125 (April 2019): 70–78. http://dx.doi.org/10.1016/j.aap.2019.01.022.

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Henseler, Jörg, and Wynne W. Chin. "A Comparison of Approaches for the Analysis of Interaction Effects Between Latent Variables Using Partial Least Squares Path Modeling." Structural Equation Modeling: A Multidisciplinary Journal 17, no. 1 (January 8, 2010): 82–109. http://dx.doi.org/10.1080/10705510903439003.

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Meehan, Jeffrey C., and Gregory L. Stuart. "Using Structural Equation Modeling With Forensic Samples." Criminal Justice and Behavior 34, no. 12 (December 2007): 1560–87. http://dx.doi.org/10.1177/0093854807307026.

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Because of its many advantages, structural equation modeling (SEM) has been used with increasing frequency in behavioral science, and it is a set of techniques that can be useful in analyzing forensic research data. Issues in SEM, including theory, estimation method, sample size and data requirements, identification, and fit indices are discussed. Using a sample of data from men arrested for domestic violence perpetration and court referred to treatment, examples of path analysis, confirmatory factor analysis, and full structural models with latent variables are presented.

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Gal, Peter, Attila Jambor, and Sandor Kovacs. "Regional determinants of Hungarian wine prices: The role of geographical indications, objective quality and individual reputation." Wine Economics and Policy 10, no. 1 (April 27, 2021): 119–32. http://dx.doi.org/10.36253/wep-8880.

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Analysing the determinants of wine prices has always been a field of interest in the wine economics literature. By estimating hedonic price functions, however, most papers generally remain at the country level with regions generally neglected or treated as simple dummy variables. The aim of this paper is to analyse the determinants of wine prices at the regional level by using Latent Variable Path Modelling with Partial Least Squares and Principal Component Analysis on the example of Hungarian wines. This approach is able to capture the regional specialties of wine production and provides a better insight into price determination. Results suggest that intrinsic values play a major but ambiguous role in determining regional wine prices, especially in the case of sugar content. It also becomes apparent that specific Geographical Indications (GIs) play a crucial role in price determination, instead of GI use per se. Moreover, individual brands also have an important role, as Tier1 and Tier2 wineries tend to sell their wines at higher prices and in smaller batch sizes.

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Jenatabadi, Hashem Salarzadeh, Che Wan Jasimah Wan Mohamed Radzi, Suzana Ariff Azizan, Maisarah Binti Hasbullah, Mohd Zufri Mamat, and Peyman Babashamsi. "Knowledge Management in Collaborative Manufacturing Food Companies Performances: Twin Impacts of Learning and Innovation." Modern Applied Science 10, no. 8 (June 18, 2016): 161. http://dx.doi.org/10.5539/mas.v10n8p161.

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The purpose of this approach is to establish the twin impacts of organizational innovation (OI) with organizational learning (OL) in the relation between knowledge management (KM) and organizational performance (OP). 168 companies of manufacturing Food Company were chosen from Malaysia, Taiwan, China and path analysis is used to analyse the underlying hypotheses. The research framework under study contain four latent variables (OP; OL; KM; OI) and three observed indicators (firm type; firm size; firm age). Structural equation modelling include mediation and moderation analysis were used in this study. The obtained results support the literature regarding the relationship among these four constructs and prove that the combination of OI and OL is mediator in the linkage between KM and firm performance. Moreover, firm age, size and type are acting as moderators among the research latent variables. The introduced model can be consider as a basic framework for technology management modelling studies. Limitation and implications for future studies are discussed.

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Journal articles on the topic 'Latent variable path analysis'

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