Two-stage Meta-analytic Structural Equation Modeling Research Articles

Examining the Differential Effectiveness of Fear Appeals in Information Security Management Using Two-Stage Meta-Analysis

ABSTRACT Most of the information security management research involving fear appeals is guided by either protection motivation theory or the extended parallel processing model. Over time, extant research has extended these theories, as well as their derivative theories, in a variety of ways, leading to several theoretical and empirical inconsistencies. The large body of fragmented, and sometimes conflicting, research has muddied the broader understanding of what drives protection- and defensive motivation. We provide guidance to the security discourse by offering the first study in the literature to employ two-stage meta-analytic structural equation modeling (TSSEM), which combines covariance-based structural equation modeling and meta-analysis. Information systems (IS) researchers have traditionally used meta-analysis for structural equation modeling for such purposes—an approach that has several serious statistical flaws. Using 341 systematically selected empirical security articles (representing 383 unique studies) and TSSEM, we pool a large series of five datasets to test six models, from which we examine the effects of constructs and paths in the security fear-appeals literature. We compare and test six versions of models inspired by issues in the broader fear-appeals literature. We confirm the importance of both the threat- and coping-appraisal processes; establish the central role of fear and that it has greater importance than threat; show that efficacy is a stronger predictor of protection motivation than is threat; demonstrate that response costs as currently measured are ineffective but that maladaptive rewards have a strong negative effect on protection motivation and a positive effect on defensive motivation; and provide evidence that dual models of danger control and fear control should be used.

The Mediating Effect of Parenting Stress on the Relationship Between Social Support and Quality of Life in Parents of Children With Autistic Spectrum Disorder: A Meta-Analytic Structural Equation Modeling.

ObjectiveThe aim of the present study is to investigate whether parenting stress mediate the relationship between social support and quality of life in parents of children with Autistic Spectrum Disorder. In addition, we examined what other variables moderate the relationships in this mediation model.MethodsUsing the two-stage meta-analytic structural equation modeling approach (MASEM), 44 correlation matrices were synthesized from 28 empirical studies (N = 13,270) and fitted to the hypothesized mediation model.ResultsThere is a significant partial mediation effect of parenting stress on the relationship between social support and quality of life. Subgroup analysis through the first stage analysis suggested that social support measurements, parental role, and child's age moderated the relationship between social support and parenting stress, and that the focus of quality of life moderated the relationship between social support and quality of life. Subgroup analysis through the second stage analysis indicated that parenting stress had a significantly stronger predictive effect on quality of life in Western culture, while the predictive effect of social support on quality of life was significantly stronger in Eastern culture.ConclusionHaving more social support can reduce parents' stress and then improving their quality of life, which can help them cope more positively and effectively with their autistic children.

Conflict and performance in channels: a meta-analysis.

Conflict between channel members is of great interest to marketers given its presumed negative impact on the channel’s business performance. In a comprehensive meta-analysis of the empirical literature spanning six decades between 1960 and 2020, we observe channel performance is indeed negatively linked to channel conflict. However, we find that this conflict–performance link has evolved significantly over time, roughly in keeping with the growth and maturing of e-commerce technologies. Further, the damage caused by conflict appears to be more pronounced for channels with international operations, and for channels with greater dependency between channel members. Additionally, businesses in North America seem to suffer the consequences of channel conflict more than others. Our results also show several study characteristics related to measurement and sampling significantly impact the empirical conflict–performance links reported in the literature. We base our conclusions on correlational analyses, two-stage meta-analytic structural equation modeling (TSSEM), and meta-analytic regression analyses (MARA).Supplementary InformationThe online version of this article (10.1007/s11747-020-00751-1) contains supplementary material, which is available to authorized users.

Investigating the Unique Predictors of Word-Problem Solving Using Meta-Analytic Structural Equation Modeling

The purpose of the present study is to clarify the contributions of cognitive skills (nonverbal reasoning, language comprehension, working memory, attention, processing speed) and academic skills (mathematics facts retrieval, mathematics computation, mathematics vocabulary, reading comprehension) in performing mathematics word problems among elementary school students. With the two-stage meta-analytic structural equation modeling approach, I synthesized 112 correlation matrices from 98 empirical studies (N = 111,346) and fitted the hypothesized partial mediation model. Overall, path analysis indicated that language comprehension, working memory, attention, mathematics vocabulary, and mathematics computation were unique predictors of word-problem solving. Subgroup analysis demonstrated different unique predictors for younger and older students to perform word problems (K-2nd grades versus 3rd–5th grades). Implications, limitations, and future directions are discussed.

Relationships on the rocks: A meta-analysis of romantic partner effects on alcohol use.

The partner influence hypothesis postulates one partner's alcohol use influences the other partner's alcohol use over time. Although several studies have examined the partner influence hypothesis, the magnitude and gender-specific nature of partner influences on alcohol use are unclear and have yet to be examined meta-analytically. We addressed this by conducting a traditional bivariate meta-analysis and two-stage meta-analytic structural equation modeling across 17 studies (N = 10,553 couples). Studies that assessed both romantic partners' alcohol use at a minimum of two time-points were selected. Results suggest romantic partners do influence one another's drinking, to a small but meaningful degree, with women (β = .19) exerting a statistically stronger (p < .05) influence than men (β = .12). Results also suggest time lag between assessment, alcohol indicator, married, and year of publication may moderate partner influence. Thus, social influences on individual alcohol use include important partner influences. These influences can serve either risk or protective functions. Given the economic, social, and health consequences associated with alcohol misuse, advancing knowledge of social risk factors for alcohol misuse is essential. Therefore, assessment and treatment of alcohol misuse should extend beyond the person to the social context. We encourage clinicians to consider involving romantic partners when assessing and treating alcohol misuse. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Dataset of parenting practices, self-control and anti-social behaviors: Meta-analytic structural equation modeling.

This dataset is used to clarify the nexus between effective parenting practices, low self-control, and anti-social behaviors in Gottfredson and Hirschi's General Theory of Crime (GTC). The analysis included 72 articles reporting 255 effect sizes (N = 94,604). We used the method of Meta-Analytic Structural Equation Modeling (MASEM) to test the assumptions of GTC. In this regard, we employed Two-Stage Meta-Analytic Structural Equation Modeling (TSSEM) and One Stage Meta-Analytic Structural Equation Modeling (OSMASEM) to perform MASEM and its moderators. The findings of the MASEM revealed that low self-control is a positive and in magnitude modest determinant of anti-social behaviors. The effective parenting practice is negative, of small size, and also a statistically significant determinant of low self-control. We observed that effective parenting practice is statistically significant and, in magnitude, shows small size negative direct and indirect effects on anti-social behaviors. That is, low self-control partially mediated the relationship between effective parenting practices and anti-social behaviors. Consistent with the construct of aggregated effective parenting practices, we found uniform patterns for models performed across the elements of effective parenting practices (i.e., emotionally supportive practices, monitoring, recognition, and effective discipline) with low self-control and anti-social behaviors. The findings of moderator analyses showed that the association between low self-control and anti-social behaviors tended to be stronger when the individualistic score of countries improved.

Reconsidering the RBANS Factor Structure: a Systematic Literature Review and Meta-Analytic Factor Analysis.

The primary aim was toperform a systematic literature review and extract data necessary for a meta-analytic factor analysis of the RBANS. Secondary aims were to examine the potential validity and utility of the resulting factor structure. Literature was identified through a review of PsycINFO, PubMed, MEDLINE, Academic Search Complete, Psychology & Behavioral Sciences Collection, CINAHL Complete, Health Source: Nursing/Academic Edition, and SocINDEX. A two-stage meta-analytic structural equation modeling method was implemented to pool correlation matrices from primary studies and perform confirmatory factor analyses. Following model selection, factor scores were computed for two datasets and subjected to correlation and diagnostic accuracy analyses. A pooled correlation matrix was computed from 24 sample correlation matrices (N = 5299). Confirmatory factor analysis revealed that the theoretical five-factor model produced the best fit but only when error terms between Story Memory and Story Recall as well as between Figure Copy and Figure Recall were included. Regression-based factor scores showed mixed relationships with the manual-defined indices, and the overall diagnostic accuracy of the factor scores was adequate in both samples examined (AUC = 0.71 and 0.87). The five-factor model was an unexpected result given the failure of multiple previous studies to find support for that model. The five-factor model demonstrates several areas of potential improvement, including better representation of the factors by the indicators. The factor scores implied by this model also require further validation.

Psychological Ownership: A Meta-Analysis and Comparison of Multiple Forms of Attachment in the Workplace

This quantitative review systematically integrates the antecedents and outcomes of psychological ownership (PO) and examines its incremental validity and explanatory power compared with two other forms of workplace attachment (i.e., organizational commitment and organizational identification). Across 141 studies published over 20 years, our meta-analysis shows that apart from the factors related to the three traditional categories of PO antecedents (i.e., control, knowing, and investment), safety (e.g., organizational justice, trust, perceived organizational support, and relational closeness) is an emerging antecedent leading to PO. In addition, we find that PO is related not only to employees’ attitudinal and performance outcomes but also to some dark-side outcomes (e.g., territorial behaviors). Furthermore, after applying two advanced methods, that is, two-stage meta-analytic structural equation modeling and dominance analysis, to the analysis of 294 studies (including 291 primary studies and three published meta-analyses), the results reveal that PO has an incremental validity above that of organizational commitment and organizational identification in predicting employees’ in-role performance and organizational citizenship behaviors. Theoretical and practical implications are discussed.

Testing IB theories with meta-analytic structural equation modeling

Purpose The purpose of this paper is to illustrate how international business (IB) researchers can benefit from meta-analytic structural equation modeling (MASEM) by introducing a statistically rigorous approach (i.e. two-stage meta-analytic structural equation modeling or TSSEM) and comparing it with a conventional approach (i.e. the univariate-r approach). The illustration and comparison present a methodological overview of MASEM that will assist IB researchers in selecting an optimal method. Design/methodology/approach In this paper, the MASEM method is elaborated upon, and methodological issues are addressed, by comparing the TSSEM and the univariate-r approaches using an empirical illustration. In this illustrative example, which is based on transaction cost economics, the effects of a firm’s internal factors on its levels of commitment in an international entry strategy are examined. Findings The MASEM method can help IB researchers to test and build on IB theories by synthesizing findings in the extant literature because this method reflects the theoretical complexity of IB (e.g. intercorrelationships among factors). Comparing the two approaches of MASEM, it is found in this study that due to its statistical rigorousness TSSEM has methodological advantages in helping IB researchers test theoretical models. Originality/value This is the first study to introduce MASEM into the discipline of IB strategies. In this paper, the authors introduce an advanced research method and illustrate two ways of using it.

Fitting meta-analytic structural equation models with complex datasets.

A modification of the first stage of the standard procedure for two-stage meta-analytic structural equation modeling for use with large complex datasets is presented. This modification addresses two common problems that arise in such meta-analyses: (a) primary studies that provide multiple measures of the same construct and (b) the correlation coefficients that exhibit substantial heterogeneity, some of which obscures the relationships between the constructs of interest or undermines the comparability of the correlations across the cells. One component of this approach is a three-level random effects model capable of synthesizing a pooled correlation matrix with dependent correlation coefficients. Another component is a meta-regression that can be used to generate covariate-adjusted correlation coefficients that reduce the influence of selected unevenly distributed moderator variables. A non-technical presentation of these techniques is given, along with an illustration of the procedures with a meta-analytic dataset. Copyright © 2016 John Wiley & Sons, Ltd.

Testing Theoretical Models with the Two-Stage Meta-Analytic Structural Equation Modeling

This paper illustrates how management researchers can benefit from a two- stage meta-analytic structural equation modeling (TSSEM) method. We address this by introducing this method in stages as we...