Counterpoint

Studying and modeling theoretical concepts is a cornerstone activity in information systems (IS) research. Researchers have been familiar with one type of theoretical concept, namely behavioral concepts, which are assumed to exist in nature and measured by a set of observable variables. In this paper, we present a second type of theoretical concept, namely forged concepts, which are designed and assumed to emerge within their environment. While behavioral concepts are classically operationalized as latent variables, forged concepts are better specified as emergent variables. Additionally, we propose composite-based structural equation modeling (SEM) as a subtype of SEM that is eminently suitable to analyze models containing emergent variables. We shed light on the composite-based SEM steps: model specification, model identification, model estimation, and model assessment. Then, we present an illustrative example from the domain of IS research to demonstrate these four steps and show how modeling with emergent variables proceeds.

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Study on the Integrated Method of SEM and DEMATEL

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.926-930.3722 ◽

2014 ◽

Vol 926-930 ◽

pp. 3722-3727

Author(s):

Wei Meng

Keyword(s):

Decision Making ◽

Structural Equation Modeling ◽

Structural Equation ◽

Model Fitting ◽

Assessment Model ◽

Model Specification ◽

Equation Modeling ◽

Model Assessment ◽

Integrated Method ◽

Model Modification

This paper compares Structural Equation Modeling and Decision Making Trial and Evaluation Laboratory. Structural Equation Modeling and Decision Making Trial and Evaluation Laboratory are all methods to study factors’ structure problem. Some steps of the two methods can completely replace each other and complement each other. This paper puts forward an integrated method of Structural Equation Modeling and Decision Making Trial and Evaluation Laboratory that includes competing model specification, model fitting, model assessment, model modification and result explain.

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A Tutorial in Bayesian Mediation Analysis With Latent Variables

Methodology ◽

10.1027/1614-2241/a000177 ◽

2019 ◽

Vol 15 (4) ◽

pp. 137-146 ◽

Cited By ~ 2

Author(s):

Milica Miočević

Keyword(s):

Mediation Analysis ◽

Latent Variables ◽

Structural Equation ◽

Structural Equation Models ◽

Estimation Method ◽

Model Specification ◽

Equation Modeling ◽

Ml Estimation ◽

Definition Of ◽

Bayesian Mediation

Abstract. Maximum Likelihood (ML) estimation is a common estimation method in Structural Equation Modeling (SEM), and parameters in such analyses are interpreted using frequentist terms and definition of probability. It is also possible, and sometimes more advantageous ( Lee & Song, 2004 ; Rindskopf, 2012 ), to fit structural equation models in the Bayesian framework ( Kaplan & Depaoli, 2012 ; Levy & Choi, 2013 ; Scheines, Hoijtink, & Boomsma, 1999 ). Bayesian mediation analysis has been described for manifest variable models ( Enders, Fairchild, & MacKinnon, 2013 ; Yuan & MacKinnon, 2009 ). This tutorial outlines considerations in the analysis and interpretation of results for the single mediator model with latent variables. The reader is guided through model specification, estimation, and the interpretations of results obtained using two kinds of diffuse priors and one set of informative priors. Recommendations are made for applied researchers and annotated syntax is provided in R2OpenBUGS and Mplus. The target audience for this article are researchers wanting to learn how to fit the single mediator model as a Bayesian SEM.

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10. Using Instrumental Variable Tests to Evaluate Model Specification in Latent Variable Structural Equation Models

Sociological Methodology ◽

10.1111/j.1467-9531.2009.01217.x ◽

2009 ◽

Vol 39 (1) ◽

pp. 327-355 ◽

Cited By ~ 32

Author(s):

James B. Kirby ◽

Kenneth A. Bollen

Keyword(s):

Latent Variables ◽

Latent Variable ◽

Structural Equation ◽

Structural Equation Models ◽

Model Specification ◽

Equation Modeling ◽

Monte Carlo Experiment ◽

Full Information ◽

Limited Information ◽

Finite Sample

Structural equation modeling (SEM) with latent variables is a powerful tool for social and behavioral scientists, combining many of the strengths of psychometrics and econometrics into a single framework. The most common estimator for SEM is the full-information maximum likelihood (ML) estimator, but there is continuing interest in limited information estimators because of their distributional robustness and their greater resistance to structural specification errors. However, the literature discussing model fit for limited information estimators for latent variable models is sparse compared with that for full-information estimators. We address this shortcoming by providing several specification tests basedon the 2SLS estimator for latent variable structural equation models developed by Bollen (1996). We explain how these tests can be used not only to identify a misspecified model but to help diagnose the source of misspecification within a model. We present and discuss results from a Monte Carlo experiment designed to evaluate the finite sample properties of these tests. Our findings suggest that the 2SLS tests successfully identify most misspecified models, even those with modest misspecification, and that they provide researchers with information that can help diagnose the source of misspecification.

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Analysis of Structural Equation Modeling as a Measuring Tool for Educational Management Research

Aptisi Transactions on Management (ATM) ◽

10.33050/atm.v2i2.812 ◽

2019 ◽

Vol 2 (2) ◽

pp. 129-139

Author(s):

Afiana Qanita ◽

Muhammad Faris Fadhlillah ◽

Andika Supriyana

Keyword(s):

Structural Equation Modeling ◽

Social Status ◽

Structural Equation ◽

Model Identification ◽

Model Specification ◽

Equation Modeling ◽

Test Model ◽

Literature Study ◽

Educational Management ◽

Reliability Factor

In management education and psychology there are certain concepts that cannot bewell defined and then various discussions arise about the true meaning of the concept.Concepts such as management intelligence, personality, attitudes, interests, ambitions, socialprejudice and social status are hypothetical constructs that are not available in operationalmethods that can directly measure them. Concepts such as intelligence, personality, attitudes,interests, ambitions, social prejudice, social status are hypothetical constructs that are notavailable operational methods that can directly measure them. This study aims to determine thebackground of the use of Structural Equation Modeling (SEM), understanding SEM, basicconcepts of SEM: constructs, manifest variables, validity, reliability, factor analysis, polycoriccorrelation, causal relationships, LISREL: Linear Structural Relationship, SEM procedures :definition of variance and covariance, model specifications, model identification, modelestimation, model formation, model compatibility test, model specification, LISREL programoutput. Symbols in SEM and SEM mathematical equations. The method used during this studytook place, namely using a literature study method which functions so that in research,researchers continue to add insight.

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Meta-Accuracy and Perceived Reciprocity From the Perception-Meta-Perception Social Relations Model

Social Psychology ◽

10.1027/1864-9335/a000356 ◽

2019 ◽

Vol 50 (1) ◽

pp. 24-37

Author(s):

Ben Porter ◽

Camilla S. Øverup ◽

Julie A. Brunson ◽

Paras D. Mehta

Keyword(s):

Structural Equation Modeling ◽

Social Relations ◽

Latent Variables ◽

Structural Equation ◽

Multilevel Structural Equation Modeling ◽

Equation Modeling ◽

Complete Understanding ◽

Social Relations Model ◽

Flexible Framework ◽

Multilevel Structural Equation

Abstract. Meta-accuracy and perceptions of reciprocity can be measured by covariances between latent variables in two social relations models examining perception and meta-perception. We propose a single unified model called the Perception-Meta-Perception Social Relations Model (PM-SRM). This model simultaneously estimates all possible parameters to provide a more complete understanding of the relationships between perception and meta-perception. We describe the components of the PM-SRM and present two pedagogical examples with code, openly available on https://osf.io/4ag5m . Using a new package in R (xxM), we estimated the model using multilevel structural equation modeling which provides an approachable and flexible framework for evaluating the PM-SRM. Further, we discuss possible expansions to the PM-SRM which can explore novel and exciting hypotheses.

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Connecting Climate and Communicable Disease to Penta Helix Using Hierarchical Likelihood Structural Equation Modelling

Symmetry ◽

10.3390/sym13040657 ◽

2021 ◽

Vol 13 (4) ◽

pp. 657

Author(s):

Rezzy Eko Caraka ◽

Maengseok Noh ◽

Rung-Ching Chen ◽

Youngjo Lee ◽

Prana Ugiana Gio ◽

...

Keyword(s):

Latent Variables ◽

Structural Equation ◽

Healthy Lifestyle ◽

Communicable Disease ◽

Well Being ◽

Equation Modeling ◽

Human Beings ◽

The Sustainable Development ◽

Healthcare Facilities ◽

Hierarchical Likelihood

Design: Health issues throughout the sustainable development goals have also been integrated into one ultimate goal, which helps to ensure a healthy lifestyle as well as enhances well-being for any and all human beings of all social level. Meanwhile, regarding the clime change, we may take urgent action to its impacts. Purpose: Nowadays, climate change makes it much more difficult to control the pattern of diseases transmitted and sometimes hard to prevent. In line with this, Centres for Disease Control (CDC) Taiwan grouped the spread of disease through its source in the first six main groups. Those are food or waterborne, airborne or droplet, vector-borne, sexually transmitted or blood-borne, contact transmission, and miscellaneous. According to this, academics, government, and the private sector should work together and collaborate to maintain the health issue. This article examines and connects the climate and communicable aspects towards Penta-Helix in Taiwan. Finding: In summary, we have been addressing the knowledge center on the number of private companies throughout the health care sector, the number of healthcare facilities, and the education institutions widely recognized as Penta Helix. In addition, we used hierarchical likelihood structural equation modeling (HSEMs). All the relationship variables among climate, communicable disease, and Penta Helix can be interpreted through the latent variables with GoF 79.24%.

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A Study on Supply–Demand Satisfaction of Community-Based Senior Care Combined with the Psychological Perception of the Elderly

Healthcare ◽

10.3390/healthcare9060643 ◽

2021 ◽

Vol 9 (6) ◽

pp. 643

Author(s):

Jiangang Shi ◽

Wenwen Hua ◽

Daizhong Tang ◽

Ke Xu ◽

Quanwei Xu

Keyword(s):

Latent Variables ◽

Structural Equation ◽

Care Service ◽

Elderly Care ◽

The Elderly ◽

Living Environment ◽

Equation Modeling ◽

Strategic Decisions ◽

Community Based ◽

The Government

Based on Maslow’s hierarchy of needs theory and customer satisfaction theory, we constructed a satisfaction model for supply–demand satisfaction for community-based senior care (SSCSC) combined with the psychological perspective of the elderly, and four dimensions of basic living needs (BLNs), living environment (LE), personal traits (PTs), and livability for the aged (LA) were selected to construct the model. The data were obtained from 296 questionnaires from seniors over 50 years old (or completed by relatives on their behalf, according to their actual situation). Twenty-two observed variables were selected for the five latent variables, and their interactions were explored using structural equation modeling. The results showed that LA was the most significant factor influencing SSCSC, and it was followed by BLNs and LE. PTs did not show a direct effect on LA, but they could have an indirect effect on SSCSC through influencing BLNs and LE. Based on the current state of community aging satisfaction, we propose to establish a community elderly care service system based on the basic needs of the elderly population, providing differentiated and refined elderly care services and improving the level of aging-friendly communities. This study provides references for the government to formulate relevant policies and other supply entities to make strategic decisions and has important implications for further enhancing community elderly services to become an important part of the social security system for the elderly.

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Building a Model of Family Caregiving for Children with Emotional Disorders

Journal of Emotional and Behavioral Disorders ◽

10.1177/106342669700500302 ◽

1997 ◽

Vol 5 (3) ◽

pp. 138-148 ◽

Cited By ~ 19

Author(s):

Thomas P. Mcdonald ◽

Thomas K. Gregoire ◽

John Poertner ◽

Theresa J. Early

Keyword(s):

Structural Equation Modeling ◽

Emotional Disorders ◽

Problem Behaviors ◽

Family Caregiving ◽

Latent Variables ◽

Structural Equation ◽

Empirical Literature ◽

Equation Modeling ◽

Special Challenge ◽

And Coping

In this article we describe the results of an ongoing effort to better understand the caregiving process in families of children with severe emotional problems. We make two assumptions. First, we assume that these families are essentially like other families but are faced with a special challenge in raising and caring for their special children while at the same time performing the multiple tasks and demands faced by all families. Second, we assume that public policy and programs must be supportive of the care of these children in their own homes and communities whenever possible. The purpose of this article is to present a model of family caregiving that draws broadly from available theory and empirical literature in multiple fields and to subject this model to empirical testing. We use structural equation modeling with latent variables to estimate an empirical model based on the theoretical model. Results of the model testing point to the importance of the child's external problem behaviors and the family's socioeconomic status and coping strategies as determinants of caregiver stress. Other findings highlight difficulties in measuring and modeling the complex mediating process, which includes formal and informal supports, perceptions, and coping behaviors. The use of structural equation modeling can benefit our efforts to support families by making explicit our theories about the important dimensions of this process and the relationship between these dimensions, which can then be subjected to measurement and validation.

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Structural Equation Modeling for the Effect of Main Factors on Abortion Issue

Journal of Raparin University ◽

10.26750/vol(7).no(1).paper1 ◽

2019 ◽

Vol 7 (1) ◽

pp. 1-13

Author(s):

Aras Jalal Mhamad ◽

Renas Abubaker Ahmed

Keyword(s):

Structural Equation Modeling ◽

Latent Variables ◽

Latent Variable ◽

Structural Equation ◽

Close Contact ◽

Maternity Hospital ◽

Equation Modeling ◽

Research Model ◽

Statistical Tools ◽

Main Factors

Based on medical exchange and medical information processing theories with statistical tools, our study proposes and tests a research model that investigates main factors behind abortion issue. Data were collected from the survey of Maternity hospital in Sulaimani, Kurdistan-Iraq. Structural Equation Modelling (SEM) is a powerful technique as it estimates the causal relationship between more than one dependent variable and many independent variables, which is ability to incorporate quantitative and qualitative data, and it shows how all latent variables are related to each other. The dependent latent variable in SEM which have one-way arrows pointing to them is called endogenous variable while others are exogenous variables. The structural equation modeling results reveal is underlying mechanism through which statistical tools, as relationship between factors; previous disease information, food and drug information, patient address, mother’s information, abortion information, which are caused abortion problem. Simply stated, the empirical data support the study hypothesis and the research model we have proposed is viable. The data of the study were obtained from a survey of Maternity hospital in Sulaimani, Kurdistan-Iraq, which is in close contact with patients for long periods, and it is number one area for pregnant women to obtain information about the abortion issue. The results shows arrangement about factors effectiveness as mentioned at section five of the study. This gives the conclusion that abortion problem must be more concern than the other pregnancy problem.

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Workload, Techno Overload, and Behavioral Stress During COVID-19 Emergency: The Role of Job Crafting in Remote Workers

Frontiers in Psychology ◽

10.3389/fpsyg.2021.655148 ◽

2021 ◽

Vol 12 ◽

Author(s):

Emanuela Ingusci ◽

Fulvio Signore ◽

Maria Luisa Giancaspro ◽

Amelia Manuti ◽

Monica Molino ◽

...

Keyword(s):

Latent Variables ◽

Structural Equation ◽

Protective Factor ◽

Two Dimensions ◽

Job Crafting ◽

Equation Modeling ◽

Work Overload ◽

Daily Work ◽

Behavioral Stress

The radical changes deriving from the COVID-19 emergency have heavily upset some of the most familiar routines of daily work life. Abruptly, many workers have been forced to face the difficulties that come with switching to remote working. Basing on the theoretical framework proposed by the Job Demands-Resources model, the purpose of this paper was to explore the effect of work overload (workload and techno overload), on behavioral stress, meant as an outcome linked to the health impairment process. Furthermore, the aim of the study was to explore the mediating role of job crafting, considered as a second-order construct consisting of two dimensions (increasing structural resources and increasing challenging demands) in the abovementioned relation. Participants were 530 workers experiencing remote working or work-from-home during the first COVID-19 lockdown in Italy (March–May 2020). Hypotheses were explored by using three different latent variables, measured reflexively through indicators on a 5-point scale, extracted from validated questionnaires. Data analysis was performed through Structural Equation Modeling; to test the mediation, bootstrap validation was computed (n = 2,000). Results showed that the mediation of job crafting was partial. More specifically, the direct effect between work overload and behavioral stress was positive; moreover, the indirect, negative effect through the mediation of job crafting was also significant. Therefore, results showed that job crafting can play a crucial role as a protective factor supporting the activation and adjustment of suitable resources; these resources can be useful to deal with the negative effects of work overload, particularly under the condition of heavy remote working and use of technologies, on individual outcomes. Starting from the current global scenario of the pandemic that has not yet ceased its effects, the study suggested decisive theoretical and practical implications. Accordingly, findings extended the current trends in occupational health psychology research, with special reference to the mainstream topic “work and COVID-19” in the Italian context. Finally, results can give suggestions to companies engaged in managing change, recommending that they build a collaborative workplace at the individual and collective level to implement job crafting interventions and enrich the personal and organizational resources of workers, which is useful cope with the current demands.

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