Correlation-Based Meta-Analytic Structural Equation Modeling: Effects of Parameter Covariance on Point and Interval Estimates

2018 ◽  
Vol 22 (4) ◽  
pp. 892-916 ◽  
Author(s):  
Shu Fai Cheung ◽  
Rong Wei Sun ◽  
Darius K.-S. Chan

More and more researchers use meta-analysis to conduct multivariate analysis to summarize previous findings. In the correlation-based meta-analytic structural equation modeling (cMASEM), the average sample correlation matrix is used to estimate the average population model. Using a simple mediation model, we illustrated that random effects covariation in population parameters can theoretically bias the path coefficient estimates and lead to nonnormal random effects distribution of the correlations. We developed an R function for researchers to examine by simulation the impact of random effects in other models. We then reanalyzed two real data sets and conducted a simulation study to examine the magnitude of the impact on realistic situations. Simulation results suggest parameter bias is typically negligible (less than .02), parameter bias and root mean square error do not differ across methods, 95% confident intervals are sometimes more accurate for the two-stage structural equation modeling approach with a diagonal random effects model, and power is sometimes higher for the traditional Viswesvaran-Ones approach. Given the increasing popularity of cMASEM in organizational research, these simulation results form the basis for us to make several recommendations on its application.

2019 ◽  
Author(s):  
Konrad Bresin

Trait impulsivity has long been proposed to play a role in aggression, but the results across studies have been mixed. One possible explanation for the mixed results is that impulsivity is a multifaceted construct and some, but not all, facets are related to aggression. The goal of the current meta-analysis was to determine the relation between the different facets of impulsivity (i.e., negative urgency, positive urgency, lack of premeditation, lack of perseverance, and sensation seeking) and aggression. The results from 93 papers with 105 unique samples (N = 36, 215) showed significant and small-to-medium correlations between each facet of impulsivity and aggression across several different forms of aggression, with more impulsivity being associated with more aggression. Moreover, negative urgency (r = .24, 95% [.18, .29]), positive urgency (r = .34, 95% [.19, .44]), and lack of premeditation (r = .23, 95% [.20, .26]) had significantly stronger associations with aggression than the other scales (rs < .18). Two-stage meta-analytic structural equation modeling showed that these effects were not due to overlap among facets of impulsivity. These results help advance the field of aggression research by clarifying the role of impulsivity and may be of interest to researchers and practitioners in several disciplines.


2021 ◽  
pp. 004728752199124
Author(s):  
Weisheng Chiu ◽  
Heetae Cho

The model of goal-directed behavior (MGB) has been widely utilized to explore consumer behavior in the fields of tourism and hospitality. However, prior studies have demonstrated inconsistent findings with respect to the causal relationships of the MGB variables. To address this issue, we conducted a meta-analytic review based on studies that had previously applied MGB. Moreover, we compared the cultural differences that emerged within MGB. By reviewing and analyzing 37 studies with 39 samples ( N = 14,581), this study found that among the causal relationships within MGB, positive anticipated emotion was the most influential determinant in the formation of consumer desire. In addition, different patterns of causal relationships between Eastern culture and Western culture were identified within MGB. This article is the first meta-analysis to address the application of MGB in tourism and hospitality and, thus, contributes to the theoretical advancement of MGB.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mazzini Muda ◽  
Muhammad Iskandar Hamzah

PurposeIn spite of the increasing organic and interactive marketing activities over social media, a general understanding of the source credibility of voluntary user-generated content (UGC) is still limited. In line with the social identity theory, this paper examines the effects of consumers' perceived source credibility of UGC in YouTube videos on their attitudes and behavioral intentions. Additionally, source homophily theory is included to predict the antecedent of source credibility.Design/methodology/approachThree hundred and seventy two Generation Y respondents were interviewed using snowball sampling. Data were analyzed with component-based structural equation modeling technique of partial least squares-structural equation modeling (PLS-SEM).FindingsFindings confirmed that perceived source credibility indirectly affects purchase intention (PI) and electronic word-of-mouth via attitude toward UGC. Besides, perceived source credibility mediates the effect of perceived source homophily on attitude toward UGC.Practical implicationsSince today's consumers have begun to trust and rely more on UGC than company-generated content on social media when making purchase decisions, companies may reconsider democratizing certain aspects of their branding strategies. Firms may fine-tune their marketing communication budgets – not only just by sponsoring public figures and celebrities but also by nurturing coproductive engagements with independent content creators who are ordinary consumers. Endowed with their imposing credibility, these micro-influencers and prosumers have high potentials to be uplifted to brand ambassadors.Originality/valueWhile consumers' purchase outcome can be measured easily using metrics and analytics, the roles of source homophily in stages leading up to the purchase is still elusive. Drawing on the rich theoretical basis of source homophily may help researchers to understand not only how credibility and attitude are related to PI but also how this nexus generates positive word of mouth among UGC followers within the social media circles.


2021 ◽  
pp. 003465432110545
Author(s):  
Xin Lin ◽  
Sarah R. Powell

In the present meta-analysis, we systematically investigated the relative contributions of students’ initial mathematics, reading, and cognitive skills on subsequent mathematics performance measured at least 3 months later. With one-stage meta-analytic structural equation modeling, we conducted analyses based on 580,437 students from 265 independent samples and 250 studies. Findings suggested fluency in both mathematics and reading, as well as working memory, yielded greater impacts on subsequent mathematics performance. Age emerged as a significant moderator in the model, such that the effects of comprehensive mathematics and working memory on subsequent mathematics increased with age, whereas attention and self-regulation’s impacts declined with age. Time lag between assessments also emerged as a significant moderator, such that the effects of word-problem solving and word recognition accuracy decreased as the time lag increased, whereas vocabulary, attention, and self-regulation’s effects increased as the time lag increased.


Author(s):  
Iin Mayasari

This study examines the model that explains the internal aspect as the stimulusi in influencing consumers to do variety seeking. The conceptual model is discussed by applying the psychology perspective of the optimum stimulation level and the impact on attitudinal loyalty. The number of questionnaires is 1100 exemplars and distributed to seven universities in Yogyakarta. However, the appropriate questionnaires to be further analyzed are 654 exemplars. The hypotheses testing uses the structural equation modeling.


2017 ◽  
Vol 11 (1) ◽  
Author(s):  
Kardison Lumban Batu

The current research is empirically investigated the impact of country of origin and consumer ethnocentrism on growing customer trend directly also through global marketing as mediating variable. It is also assessed the impact of global marketing on growing consumer trend. By deploying Structural Equation Modeling with AMOS, three independent variables were analyzed, country of origin (CoC), global marketing (GM), consumer ethnocentrism (CE) and growing consumer trend (GCT) as dependent variable. The findings showed that both country of origin (CoC) and consumer ethnocentrism (CE) have significant effect on global marketing (GM) as well as on growing consumer trend (GCT). Further, global marketing (GM) successfully mediated and showed significant effect of both country of origin and consumer ethnocentrism. Finally global marketing has significant impact on growing consume trend.


2017 ◽  
Vol 20 (1) ◽  
pp. 121 ◽  
Author(s):  
Muhammad Rasyid Abdillah ◽  
Rizqa Anita ◽  
Rita Anugerah

Penelitian ini bertujuan untuk menguji dampak iklim organisasi terhadap stres kerja dan kinerja karyawan. Data yang digunakan dalam penelitian ini adalah data primer dalam bentuk kuesioner dimana subjek penelitiannya adalah para 45 karyawan PT. Adei Plantation & Industry Head Office Pekanbaru Riau. Pengujian hipotesis menggunakan Structural Equation Modeling Partial Least Square. Hasil penelitian menunjukkan bahwa iklim organisasi berpengaruh terhadap stres kerja dan kinerja karyawan. Selain itu, hasil ini juga menunjukkan bahwa pengaruh iklim organisasi terhadap kinerja karyawan adalah pengaruh tidak langsung melalui stres kerja.This study aims to examine the impact of organizational climate on job stress and employee performance. The data used in this study was primary data in the form of a questionnaire in which the research subjects are 45 employees of PT. Adei Plantation & Industry Head Office Pekanbaru Riau. To test the hypothesis using Structural Equation Modeling Partial Least Square. The result suggest that organizational climate influence on job stress and employee performance. In addition, result also suggest that the effect of organizational climate on employee performance is indirect influence through job stress.


Author(s):  
David Opeoluwa Oyewola ◽  
Emmanuel Gbenga Dada ◽  
Juliana Ngozi Ndunagu ◽  
Terrang Abubakar Umar ◽  
Akinwunmi S.A

Since the declaration of COVID-19 as a global pandemic, it has been transmitted to more than 200 nations of the world. The harmful impact of the pandemic on the economy of nations is far greater than anything suffered in almost a century. The main objective of this paper is to apply Structural Equation Modeling (SEM) and Machine Learning (ML) to determine the relationships among COVID-19 risk factors, epidemiology factors and economic factors. Structural equation modeling is a statistical technique for calculating and evaluating the relationships of manifest and latent variables. It explores the causal relationship between variables and at the same time taking measurement error into account. Bagging (BAG), Boosting (BST), Support Vector Machine (SVM), Decision Tree (DT) and Random Forest (RF) Machine Learning techniques was applied to predict the impact of COVID-19 risk factors. Data from patients who came into contact with coronavirus disease were collected from Kaggle database between 23 January 2020 and 24 June 2020. Results indicate that COVID-19 risk factors have negative effects on epidemiology factors. It also has negative effects on economic factors.


2019 ◽  
Vol 7 (3) ◽  
pp. 0-0
Author(s):  
Mohammad Zarei Mahmoudabadi ◽  
◽  
Mohammad Keshtidar ◽  
Seyed Mohammad Javad Razavi ◽  
◽  
...  

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