scholarly journals Fitting Fixed- and Random-effects Meta-analysis Models Using Structural Equation Modeling with the Sem and Gsem Commands

2015 ◽  
Vol 15 (3) ◽  
pp. 645-671 ◽  
Author(s):  
Tom M. Palmer ◽  
Jonathan A. C. Sterne
Keyword(s):  
Structural Equation Modeling ◽  
Random Effects ◽  
Structural Equation ◽  
Meta Analysis ◽  
Equation Modeling ◽  
Fixed And Random Effects ◽  
Analysis Models

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
Keyword(s):  
Structural Equation Modeling ◽  
Random Effects ◽  
Structural Equation ◽  
Meta Analysis ◽  
Real Data ◽  
Equation Modeling ◽  
Path Coefficient ◽  
Data Sets ◽  
Simulation Results ◽  
The Impact

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.

Impulsivity and Aggression: A Meta-analysis Using the UPPS Model of Impulsivity

2019 ◽  
Author(s):  
Konrad Bresin
Keyword(s):  
Structural Equation Modeling ◽  
Sensation Seeking ◽  
Structural Equation ◽  
Meta Analysis ◽  
The Other ◽  
Equation Modeling ◽  
Negative Urgency ◽  
Two Stage ◽  
Trait Impulsivity

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.

The Model of Goal-Directed Behavior in Tourism and Hospitality: A Meta-analytic Structural Equation Modeling Approach

2021 ◽  
pp. 004728752199124
Author(s):  
Weisheng Chiu ◽  
Heetae Cho
Keyword(s):  
Structural Equation Modeling ◽  
Cultural Differences ◽  
Structural Equation ◽  
Meta Analysis ◽  
Equation Modeling ◽  
Causal Relationships ◽  
Eastern Culture ◽  
Analytic Review ◽  
Tourism And Hospitality ◽  
Goal Directed Behavior

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.

The Roles of Initial Mathematics, Reading, and Cognitive Skills in Subsequent Mathematics Performance: A Meta-Analytic Structural Equation Modeling Approach

2021 ◽  
pp. 003465432110545
Author(s):  
Xin Lin ◽  
Sarah R. Powell
Keyword(s):  
Working Memory ◽  
Structural Equation Modeling ◽  
Cognitive Skills ◽  
Structural Equation ◽  
Meta Analysis ◽  
Time Lag ◽  
Mathematics Performance ◽  
Equation Modeling ◽  
Word Problem Solving ◽  
Significant Moderator

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.

scholarly journals Development of model poverty in Java using Meta-Analysis Structural Equation Modeling (MASEM)

2019 ◽  
Author(s):  
Bambang Widjanarko Otok ◽  
Rahmawati Erma Standsyah ◽  
Agus Suharsono ◽  
Purhadi
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Meta Analysis ◽  
Equation Modeling

scholarly journals Structural Equation Modeling (SEM)-Based Meta-Analysis

2021 ◽  
Author(s):  
Mike W.-L. Cheung
Keyword(s):  
Social Sciences ◽  
Structural Equation Modeling ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Meta Analysis ◽  
Equation Model ◽  
Equation Modeling ◽  
Future Directions ◽  
Software Packages ◽  
Meta Analyses

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.

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