scholarly journals Some Reflections on Combining Meta-Analysis and Structural Equation Modeling

2018 ◽  
Author(s):  
Mike W.-L. Cheung

Meta-analysis and structural equation modeling (SEM) are two of the most prominent statistical techniques employed in the behavioral, medical, and social sciences. They each have their own well-established research communities, terminologies, statistical models, software packages, and journals (Research Synthesis Methods and Structural Equation Modeling: A Multidisciplinary Journal). In this paper, I will provide some personal reflections on combining meta-analysis and SEM in the forms of meta-analytic SEM (MASEM) and SEM-based meta-analysis. The critical contributions of Becker (1992), Shadish (1992), and Viswesvaran and Ones (1995) in the early development of MASEM are highlighted. Another goal of the paper is to illustrate how meta-analysis can be extended and integrated with other techniques to address new research questions such as the analysis of Big Data. I hope that this paper may stimulate more research development in the area of combining meta-analysis and SEM.

2021 ◽  
Author(s):  
Mike W.-L. Cheung

Structural equation modeling (SEM) and meta-analysis are two popular techniques in the behavioral, medical, and social sciences. They have their own research communities, terminologies, models, software packages, and even journals. This chapter introduces SEM-based meta-analysis, an approach to conduct meta-analyses using the SEM framework. By conceptualizing studies in a meta-analysis as subjects in a structural equation model, univariate, multivariate, and three-level meta-analyses can be fitted as structural equation models using definition variables. We will review fixed-, random-, and mixed-effects models using the SEM framework. Examples will be used to illustrate the procedures using the metaSEM and OpenMx packages in R. This chapter closes with a discussion of some future directions for research.


1994 ◽  
Vol 21 (3) ◽  
pp. 179-181 ◽  
Author(s):  
James B. Hittner ◽  
Kenneth M. Carpenter

We describe software and present theoretical and applied sources for teaching a graduate course in structural equation modeling. We recommend Linear Structural Relations (LISREL; Jöreskog & Sörbom, 1989) as the primary structural equation modeling software because it is the most generally applicable and widely available of the appropriate software packages, and it is fully supported by the Statistical Package for the Social Sciences (SPSS, 1988). We also suggest relevant background readings, recommend principal textbook sources and review articles, and advocate reading empirical journal articles to accompany the core texts. These sources are offered as part of a comprehensive teaching approach designed to impart an appreciation for and working knowledge of LISREL-based structural equation modeling.


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 ◽  
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.


2019 ◽  
Author(s):  
Bambang Widjanarko Otok ◽  
Rahmawati Erma Standsyah ◽  
Agus Suharsono ◽  
Purhadi

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