scholarly journals Higher-Order PLS-PM Approach for Different Types of Constructs

2020 ◽  
Author(s):  
Corrado Crocetta ◽  
Laura Antonucci ◽  
Rosanna Cataldo ◽  
Roberto Galasso ◽  
Maria Gabriella Grassia ◽  
...  
Keyword(s):  
Structural Equation ◽  
Structural Equation Models ◽  
Higher Order ◽  
Complex Phenomenon ◽  
Path Modeling ◽  
Empirical Application ◽  
Measurement Models ◽  
Different Types ◽  
Complex Models ◽  
Reflective Measurement

AbstractPartial least squares path modeling (PLS-PM) has become very popular in recent years, for measuring concepts that depend on different aspects and that are based on different types of relationships. PLS-PM represents a useful tool to explore relationships and to analyze the influence of the different aspects on the complex phenomenon analyzed. In particular, the use of higher-order constructs has allowed researchers to extend the application of PLS-PM to more advanced and complex models. In this work, our attention is focused on higher-order constructs that include reflective or formative relationships. Even if the dispute between formative models and reflective models is not exactly recent, it is still alive in current literature, for the most part within the context of structural equation models. This paper focuses attention on theoretical and mathematical differences between formative and reflective measurement models within the context of the PLS-PM approach. A simulation study is proposed in order to show how these approaches fit well in different modeling situations. The approaches have been compared using empirical application in a sustainability context. The findings from the simulation and the empirical application can help researchers to estimate and to use the higher-order PLS-PM approach in reflective and formative type models.

Forced Zero Cross-Loading Misspecifications in Measurement Component of Structural Equation Models

Methodology ◽  
2014 ◽  
Vol 10 (4) ◽  
pp. 138-152 ◽  
Author(s):  
Hsien-Yuan Hsu ◽  
Susan Troncoso Skidmore ◽  
Yan Li ◽  
Bruce Thompson
Keyword(s):  
Structural Equation ◽  
Structural Model ◽  
Structural Equation Models ◽  
Equation Model ◽  
Model Fit ◽  
Model Specification ◽  
Simulation Design ◽  
Measurement Models ◽  
Fit Statistics ◽  
Path Coefficients

The purpose of the present paper was to evaluate the effect of constraining near-zero parameter cross-loadings to zero in the measurement component of a structural equation model. A Monte Carlo 3 × 5 × 2 simulation design was conducted (i.e., sample sizes of 200, 600, and 1,000; parameter cross-loadings of 0.07, 0.10, 0.13, 0.16, and 0.19 misspecified to be zero; and parameter path coefficients in the structural model of either 0.50 or 0.70). Results indicated that factor pattern coefficients and factor covariances were overestimated in measurement models when near-zero parameter cross-loadings constrained to zero were higher than 0.13 in the population. Moreover, the path coefficients between factors were misestimated when the near-zero parameter cross-loadings constrained to zero were noteworthy. Our results add to the literature detailing the importance of testing individual model specification decisions, and not simply evaluating omnibus model fit statistics.

scholarly journals Gender-specific patterns and determinants of spillover between work and family: The role of partner support in dual-earner couples

2020 ◽  
Vol 33 (1) ◽  
pp. 72-98
Author(s):  
Ayhan Adams ◽  
Katrin Golsch
Keyword(s):  
Structural Equation ◽  
Structural Equation Models ◽  
Work And Family ◽  
Partner Support ◽  
Full Time ◽  
Family Conflicts ◽  
Dual Earner ◽  
Different Types ◽  
Gender Specific

Objective: The study investigates how partner support affects different types of work-to-family and family-to-work conflicts in dual-earner couples divided by gender and parenthood. Background: In Germany, as in other Western Countries, interrole conflicts between work and family increase, especially within dual-earner couples. Only few studies focused on the effects of partner support on different types of these conflicts. Method: We use longitudinal data deriving from waves 6 to 10 of the German Family Panel (pairfam) to uncover the extent to which the perception of having a supportive partner reduces time- and strain-based work-to-family and family-to-work conflicts. We conduct longitudinal structural equation models based on information of 1,252 persons, which are full-time employed and live in a dual-earner relationship. Results: Whereas for men partner support helps reduce stress-based work-to-family conflicts, for women perceived partner support is not beneficial. Within a subsample of parents, the experience of work-to-family conflicts is likely irrespective of partner support. Overall, women’s family-to-work conflicts appear to be reduced by their partners’ support whereas for men this detrimental effect only applies in the case of stress-based family-to-work conflicts. Conclusion: To sum up the findings, the differences for men and women in the effect of partner support on different types of interrole conflicts indicate a still existing impact of traditional gender norms that connect femininity to house work and masculinity to employed work.

Estimating Multilevel Linear Models as Structural Equation Models

2003 ◽  
Vol 28 (2) ◽  
pp. 135-167 ◽  
Author(s):  
Daniel J. Bauer
Keyword(s):  
Structural Equation ◽  
Linear Models ◽  
Structural Equation Models ◽  
Broad Class ◽  
Causal Chain ◽  
Latent Factors ◽  
Measurement Models ◽  
Multiple Indicator ◽  
Current Article ◽  
Multilevel Linear Models

Multilevel linear models (MLMs) provide a powerful framework for analyzing data collected at nested or non-nested levels, such as students within classrooms. The current article draws on recent analytical and software advances to demonstrate that a broad class of MLMs may be estimated as structural equation models (SEMs). Moreover, within the SEM approach it is possible to include measurement models for predictors or outcomes, and to estimate the mediational pathways among predictors explicitly, tasks which are currently difficult with the conventional approach to multilevel modeling. The equivalency of the SEM approach with conventional methods for estimating MLMs is illustrated using empirical examples, including an example involving both multiple indicator latent factors for the outcomes and a causal chain for the predictors. The limitations of this approach for estimating MLMs are discussed and alternative approaches are considered.

scholarly journals The SEMinR Package

2021 ◽  
pp. 49-74
Author(s):  
Joseph F. Hair ◽  
G. Tomas M. Hult ◽  
Christian M. Ringle ◽  
Marko Sarstedt ◽  
Nicholas P. Danks ◽  
...  
Keyword(s):  
Least Squares ◽  
Structural Equation Model ◽  
Software Package ◽  
Structural Equation ◽  
Structural Model ◽  
Structural Equation Models ◽  
Equation Model ◽  
Quality Reporting ◽  
Measurement Models ◽  
User Friendly

AbstractSEMinR is a software package developed for the R statistical environment (R Core Team, 2021). The package includes a user-friendly syntax for creating and estimating structural equation models using estimators such as partial least squares. In this chapter, we introduce the syntax to create, estimate, and report structural equation models using SEMinR. We demonstrate the four steps to specifying and estimating a structural equation model: (1) loading and cleaning the data, (2) specifying the measurement models, (3) specifying the structural model, and (4) estimating, bootstrapping, and summarizing the model. This chapter also describes how to export results and figures from R for professional, publication-quality reporting.

scholarly journals T193. THE ROLE OF METACOGNITION ON NEGATIVE SYMPTOMS: A PSYCHOLOGICAL MODEL FOR DIMINISHED EXPRESSION IN SCHIZOPHRENIA

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S305-S305
Author(s):  
Helena García-Mieres ◽  
Nancy Lundin ◽  
Kyle Minor ◽  
Giancarlo DiMaggio ◽  
Simone Cheli ◽  
...  
Keyword(s):  
Cognitive Deficits ◽  
Structural Equation ◽  
Negative Symptoms ◽  
Structural Equation Models ◽  
Personal Narratives ◽  
Higher Order ◽  
Psychotic Symptoms ◽  
Situation Models ◽  
Cognitive Symptoms ◽  
The Impact

Abstract Background The resistance of negative symptoms to pharmacologic treatment has spurred interest in understanding the psychological factors that contribute to their formation and persistence. However, little is understood about the psychological processes that reinforce and sustain the negative symptoms domain of diminished expression. Prior research has shown that higher levels of diminished expression relate to deficits in metacognitive capacity. We propose a more complex model in which diminished expression occurs when impairments in metacognitive self-reflectivity, alterations in higher-order language structure, and cognitive deficits interact and thus interfere with persons’ ability to understand and express emotions in ways others can recognize. Methods Individuals with schizophrenia-spectrum disorders (N=201) provided personal narratives including their life story and reflections regarding their mental illness and a clinician-rated interview of psychotic symptoms (i.e., Positive and Negative Syndrome Scale; PANSS). Self-reflectivity was measured with the Metacognition Assessment Scale-Abbreviated, and situation models were extracted from participants’ personal narratives via Coh-Metrix 3.0, an automated program that calculates basic and complex language indices. Diminished expression and cognitive symptoms were measured with the PANSS. Structural equation models (SEM) examined whether self-reflectivity mediated the impact of cognitive deficits and situation models on diminished expression. Results SEM revealed that self-reflectivity partially mediated the impact of situation models on diminished expression (β = -.083, p = .005, ±95% CI [-.141, -.026]) and fully mediated the influence of cognitive symptoms in diminished expression (β = .099, p = .001, ±95% CI [.038, .160]). Findings persisted after controlling for educational level. Discussion This study is the first of its kind to utilize a mediational model including higher-order linguistic structures, cognitive impairment and metacognition to explain diminished expression in psychosis. Results suggest that self-reflectivity, situation models and cognitive symptoms may be useful targets for intervention in efforts to decrease diminished expression.

scholarly journals An Introduction to Structural Equation Modeling

2021 ◽  
pp. 1-29
Author(s):  
Joseph F. Hair ◽  
G. Tomas M. Hult ◽  
Christian M. Ringle ◽  
Marko Sarstedt ◽  
Nicholas P. Danks ◽  
...  
Keyword(s):  
Structural Equation Modeling ◽  
Multivariate Data Analysis ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Equation Modeling ◽  
Causal Explanations ◽  
Measurement Models ◽  
Key Characteristics ◽  
Predictive Approach ◽  
Complex Relationships

AbstractStructural equation modeling is a multivariate data analysis method for analyzing complex relationships among constructs and indicators. To estimate structural equation models, researchers generally draw on two methods: covariance-based SEM (CB-SEM) and partial least squares SEM (PLS-SEM). Whereas CB-SEM is primarily used to confirm theories, PLS represents a causal–predictive approach to SEM that emphasizes prediction in estimating models, whose structures are designed to provide causal explanations. PLS-SEM is also useful for confirming measurement models. This chapter offers a concise overview of PLS-SEM’s key characteristics and discusses the main differences compared to CB-SEM. The chapter also describes considerations when using PLS-SEM and highlights situations that favor its use compared to CB-SEM.

scholarly journals Determinants of COVID-19 Vaccine Hesitancy in Portuguese-Speaking Countries: A Structural Equations Modeling Approach

Vaccines ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1167
Author(s):  
Álvaro Francisco Lopes de Sousa ◽  
Jules Ramon Brito Teixeira ◽  
Iracema Lua ◽  
Fernanda de Oliveira Souza ◽  
Andrêa Jacqueline Fortes Ferreira ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Structural Equations ◽  
Vaccine Hesitancy ◽  
Cognitive Vulnerabilities ◽  
Measurement Models ◽  
Validated Questionnaire ◽  
Conspiracy Beliefs ◽  
Vaccination Campaigns

COVID-19 vaccine hesitancy (VH) has caused concerns due to the possible fluctuations that may occur directly impacting the control of the pandemic. In this study, we aimed to estimate the prevalence and factors associated with COVID-19 VH in Portuguese-speaking countries. We developed a web survey (N:6,843) using an online, structured, and validated questionnaire. We used Measurement Models, Exploratory Factor Analysis, Exploratory Structural Equation Models, and Confirmatory Factor Analysis for the data analysis. The overall prevalence of COVID-19 VH in Portuguese-speaking countries was 21.1%. showed a statistically significant direct effect for VH: vaccine-related conspiracy beliefs (VB) (β = 0.886), perceived stress (PS) (β = 0.313), COVID-19 Misinformation (MIS) (β = 0.259) and individual responses to COVID-19 (CIR) (β = −0.122). The effect of MIS and CIR for VH was greater among men and of PS and VB among women; the effect of PS was greater among the youngest and of VB and CIR among the oldest. No discrepant differences were identified in the analyzed education strata. In conclusion, we found that conspiracy beliefs related to the vaccine strongly influence the decision to hesitate (not to take or to delay the vaccine). Specific characteristics related to gender, age group, social and cognitive vulnerabilities, added to the knowledge acquired, poorly substantiated and/or misrepresented about the COVID-19 vaccine, need to be considered in the planning of vaccination campaigns. It is necessary to respond in a timely, fast, and accurate manner to the challenges posed by vaccine hesitancy.

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