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.

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 Language and nonlanguage factors in foreign language learning: evidence for the learning condition hypothesis

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Xin Kang ◽  
Stephen Matthews ◽  
Virginia Yip ◽  
Patrick C. M. Wong
Keyword(s):  
Language Learning ◽  
Structural Equation ◽  
Linear Models ◽  
Structural Equation Models ◽  
Foreign Language Learning ◽  
Learning Condition ◽  
Third Language ◽  
Musical Background ◽  
Learning Success ◽  
Learning Conditions

AbstractThe question of why native and foreign languages are learned with a large performance gap has prompted language researchers to hypothesize that they are subserved by fundamentally different mechanisms. However, this hypothesis may not have taken into account that these languages can be learned under different conditions (e.g., naturalistic vs. classroom settings). With a large sample of 636 third language (L3) learners who learned Chinese and English as their first (L1) and second (L2) languages, the present study examined the association of learning success across L1–L3. We argue that learning conditions may reveal how these languages are associated in terms of learning success. Because these languages were learned under a continuum of naturalistic to classroom conditions from L1 to L3, this sample afforded us a unique opportunity to evaluate the hypothesis that similar learning conditions between languages could be an important driving force determining language learning success. After controlling for nonlanguage factors such as musical background and motivational factors and using a convergence of analytics including the general linear models, the structural equation models, and machine learning, we found that the closer two languages were on the continuum of learning conditions, the stronger their association of learning success. Specifically, we found a significant association between L1 and L2 and between L2 and L3, but not between L1 and L3. Our results suggest that learning conditions may have important implications for the learning success of L1–L3.

The Financial Identity Scale (FIS): A multinational validation and measurement invariance study among emerging adults

2020 ◽  
Vol 44 (6) ◽  
pp. 565-574
Author(s):  
Angela Sorgente ◽  
Rimantas Vosylis ◽  
Margherita Lanz ◽  
Joyce Serido ◽  
Soeyon Shim
Keyword(s):  
Emerging Adults ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Sensitivity To Change ◽  
Validity And Reliability ◽  
Cross Sectional ◽  
Self Sufficiency ◽  
Current Article ◽  
Difference Criterion ◽  
Financial Identity

The transition from financial dependence on one’s parents to financial self-sufficiency is one of the most relevant transitions during emerging adulthood. It is important to have an instrument able to assess emerging adults’ financial capabilities and to detect its change over time. The current article aims to collect international evidence of the Financial Identity Scale (FIS) validity and reliability. Cross-sectional data collected from 2,501 emerging adults aged 18–25 and belonging to three different countries—U.S. ( n = 1,535), Italy ( n = 485), and Lithuania ( n = 481)—were adopted to test score structure validity, generalizability, sensitivity to difference, criterion-related validity, and internal consistency. Instead, four-wave longitudinal data, available for the American sample only ( n = 1,900), were adopted to test FIS structural stability and sensitivity to change. As recommended by the contemporary view of validity, different structural equation models were performed. Findings suggest that FIS scores are valid and reliable. The implications for researchers and practitioners are discussed.

Acceptance and use of telepsychology from patients’ perspective: perceived advantages and barriers (Preprint)

2020 ◽  
Author(s):  
Beatriz Sora ◽  
Ruben Nieto ◽  
Adrian Montesano del Campo ◽  
Manuel Armayones
Keyword(s):  
Mental Health ◽  
Structural Equation ◽  
Online Survey ◽  
Structural Equation Models ◽  
Causal Chain ◽  
Perceived Usefulness ◽  
Convenience Sample ◽  
Utaut Model ◽  
Mental Health Interventions ◽  
Patients Acceptance

BACKGROUND Telepsychology is currently incorporated in clinical practice, being offered in most psychotherapy centers. However, there seems to be a remarkable discrepancy between the offer, or interest in, and real-world uptake of e-mental health interventions among the population. A critical precondition is patients’ willingness to accept and use telepsychology, although this issue has thus far been overlooked in research. OBJECTIVE The aim of this study was to examine patients’ acceptance and use of telepsychology by adopting an extended UTAUT model that integrates perceived telepsychology advantages and barriers, usefulness perceptions, behavioral intention and telepsychology use. METHODS An online survey was conducted on a convenience sample of 514 subjects. Structural equation models were computed to test a mediation model. RESULTS Results supported the UTAUT model to explain patients’ acceptance and use of telepsychology. They showed a causal chain in which perceived telepsychology advantages and barriers were related to telepsychology use through the perceived usefulness of and intention to use telepsychology. CONCLUSIONS Telepsychology use may be explained according to the UTAUT model when coupled with patients’ perceptions of telepsychology advantages and barriers. Mental health stakeholders could consider these factors in order to increase the acceptance and use of telepsychology.

scholarly journals Mediating pathways from central obesity to childhood asthma: a population-based longitudinal study

2016 ◽  
Vol 48 (3) ◽  
pp. 748-757 ◽  
Author(s):  
An-Hsuan Chih ◽  
Yang-Ching Chen ◽  
Yu-Kang Tu ◽  
Kuo-Chin Huang ◽  
Tai-Yuan Chiu ◽  
...  
Keyword(s):  
Pulmonary Function ◽  
Childhood Asthma ◽  
Structural Equation ◽  
Central Obesity ◽  
Linear Models ◽  
Structural Equation Models ◽  
Population Based ◽  
Health Study ◽  
Respiratory Outcomes ◽  
Mediating Pathways

The mediating pathways linking obesity and asthma are largely unknown. We aimed to investigate the mediating pathways and to search for the most prominent pathological mechanism between central obesity and childhood asthma.In the Taiwan Children Health Study, we collected data on an open cohort of children aged 9–13 years. Children's respiratory outcomes, atopic conditions, obesity measures and pulmonary function were surveyed annually between 2010 and 2012. Exhaled nitric oxide fraction concentrations were recorded in 2012. Generalised estimating equations and general linear models were used to examine the associations between central obesity, possible mediators and asthma. Structural equation models were applied to investigate the pathways that mediate the link between central obesity and asthma.Central obesity (waist-to-hip ratio) most accurately predicted childhood asthma. In the active asthma model, the percentage of mediation was 28.6% for pulmonary function, 18.1% for atopy and 5.7% for airway inflammation. The percentage of mediation for pulmonary function was 40.2% in the lifetime wheeze model. Pulmonary function was responsible for the greatest percentage of mediation among the three mediators in both models.Decline in pulmonary function is the most important pathway in central obesity related asthma. Pulmonary function screening should be applied to obese children for asthma risk prediction.

Structural Equation Modeling to Determine Passenger Loyalty toward Intercity Bus Services

2005 ◽  
Vol 1927 (1) ◽  
pp. 249-255 ◽  
Author(s):  
Chieh-Hua Wen ◽  
Lawrence W. Lan ◽  
Hsiu-Ling Cheng
Keyword(s):  
Service Quality ◽  
Structural Equation ◽  
Switching Costs ◽  
Structural Equation Models ◽  
Equation Modeling ◽  
Latent Factors ◽  
Empirical Results ◽  
Service Value ◽  
Positive Effects ◽  
Bus Services

This paper investigates passenger loyalty to intercity bus services and identifies important factors influencing loyalty. The relationships between passenger loyalty and other latent factors, including satisfaction, service value, service quality, sacrifice, switching costs, attractiveness of competitors, and trust are hypothesized and tested. Factor analysis is used to extract the latent service quality factors from a large number of service quality indicators. Structural equation models are then developed to elucidate the causal relationships of passenger loyalty and the latent factors. The empirical results have confirmed the proposed hypotheses. Satisfaction has the most significant influence on passenger loyalty. Service value, switching costs, and trust have direct and positive effects on loyalty, whereas attractiveness of competitors has a direct negative effect. The indirect effect of service quality, via service value and satisfaction, on passenger loyalty is also significant. From the empirical results, managerial implications for the bus carriers are addressed.

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 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.

scholarly journals Mindfulness Is Associated With Lower Stress and Higher Work Engagement in a Large Sample of MOOC Participants

2021 ◽  
Vol 12 ◽  
Author(s):  
Larissa Bartlett ◽  
Marie-Jeanne Buscot ◽  
Aidan Bindoff ◽  
Richard Chambers ◽  
Craig Hassed
Keyword(s):  
Standard Deviation ◽  
Perceived Stress ◽  
Work Engagement ◽  
Structural Equation ◽  
Linear Models ◽  
Structural Equation Models ◽  
Cross Sectional ◽  
Large Sample ◽  
Personal Resource ◽  
Standard Deviation Unit

Objective: This study aimed to understand the associations between mindfulness, perceived stress, and work engagement in a very large sample of English-speaking adults, from 130 different countries. It also aimed to assess participants' self-reported changes following a 6-week mindfulness massive open online course (MOOC).Methods: Participants in the 6-week MOOC were invited to complete pre-post online surveys. Cross-sectional associations were assessed using univariate linear models, followed by structural equation models to test mediation pathways in baseline data (N = 16,697). Self-reported changes in mindfulness, stress and engagement following training were assessed using paired t-tests (n = 2,105).Results: Each standard deviation unit increase in mindfulness was associated with a 0.52 standard deviation unit decrease in perceived stress, and with 0.06 standard deviation unit increment in work engagement. 73% of the influence of mindfulness on engagement was direct. Following the mindfulness MOOC, participants reported higher mindfulness (d = 1.16), reduced perceived stress (d = 1.00) and a small improvement in work engagement (d = 0.29).Conclusions: Mindfulness was associated with lower perceived stress and higher work engagement in both cross-sectional and longitudinal analyses. These findings support mindfulness as a potentially protective and modifiable personal resource. The MOOC format offers a low cost, highly accessible means for extending the reach and potential benefits of mindfulness training to large numbers of people.

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