Structural equation modelling (SEM) is outlined and compared with two non-linear alternatives, artificial neural networks and ''fast and frugal'' models. One particular non-linear decision-making situation is discussed, that exemplified by a lexicographic semi-order. We illustrate the use of SEM on a dataset derived from 539 volunteers' responses to questions about food-related risks. Our conclusion is that SEM is a useful member of the armoury of techniques available to the student of human judgement: it subsumes several multivariate statistical (...) techniques and permits their flexible combination, and it provides robust goodness-of-fit statistics and is available in (generally) easy-to-use computer packages. Although the number of tasks for which SEM provides a persuasive psychological model is small, it is very useful in identifying the important variables and their inter-relations that contribute to task performance, and thus can constitute a valuable intermediate staging point between raw data and a fully fledged psychological theory. (shrink)

Structural equation model trees are data-driven tools for finding variables that predict group differences in SEM parameters. SEM trees build upon the decision tree paradigm by growing tree structures that divide a data set recursively into homogeneous subsets. In past research, SEM trees have been estimated predominantly with the R package semtree. The original algorithm in the semtree package selects split variables among covariates by calculating a likelihood ratio for each possible split of each covariate. Obtaining these likelihood (...) ratios is computationally demanding. As a remedy, we propose to guide the construction of SEM trees by a family of score-based tests that have recently been popularized in psychometrics. These score-based tests monitor fluctuations in case-wise derivatives of the likelihood function to detect parameter differences between groups. Compared to the likelihood-ratio approach, score-based tests are computationally efficient because they do not require refitting the model for every possible split. In this paper, we introduce score-guided SEM trees, implement them in semtree, and evaluate their performance by means of a Monte Carlo simulation. (shrink)

The objective of the study was to develop a structural model that explores the relationship between Mathematics Performance and students’ self-regulated learning skills, grit, and expectancy-value towards science, technology, engineering and mathematics (STEM). The research collected survey data from 664 senior high school students from 17 STEM high schools, and conducted a covariance-based structural equation modeling (SEM) analysis. The results of the SEM analysis indicate that the Re-specified Self-Regulated Learning Skill – Expectancy-Value towards STEM – Grit – (...) Mathematics Performance (Re-specified SRL-EV-GR-MP) model is the most parsimonious fit, offering the best empirical support for the theoretical model of the study. The research findings suggest that the mathematics performance of senior high school students in STEM curriculum is attributed to their high expectancies for success and perceived values of the STEM tasks, high grit, and high self-regulated learning skills. Moreover, the research also observed evidence of mediating and moderating grit effects in the concurrent effects of expectancy-values towards STEM and self-regulated learning skills towards students’ mathematics performance. (shrink)

In the article, in which religious attitudes and behaviours in rural life and agricultural activities in Antalya have been studied, the religious mentality of the farmers engaged in agricultural activities has been analysed in the context of agricultural perceptions, agricultural production problems and religious attitudes scales. Human being has cultivated the soil to meet his most basic physiological needs, and the stages in these cultivation processes constitute the development stages of human history. In this way, it could be said that (...) the history of farming is the history of humanity. Farming, which has undergone a structural transformation with mechanization, is experiencing its most difficult period in the production-health equation today. The ever-increasing population in the world has led to the need to diversify products as well as to produce more. This brought the improvement of seeds, analysis of the soil, spraying in the production process all from the traditional form to a modern form, which brought the problem of trust towards the product and the producer to the fore. In our study, which focuses on the question of what is the effect of religious attitudes on the solution of agricultural production problems, the data have been obtained through face-to-face interviews with the farmers of Antalya and three scales have been developed as agricultural perception, agricultural production problems and religious attitudes. While the agricultural perceptions scale is dealt with three stages: farmers’ perceptions of soil, profession and technology, religious attitude scale is dealt with in four stages: fate, beliefs, traditional practices, and fiqh rules. The scale of agricultural production problems is discussed as one-dimensional. Data collected through each of these three scales has been analysed with the help of standard deviation and mean, t-test results and structural equation modelling (SEM) techniques. Within the framework of the structural equation model, four hypotheses have been developed and these hypotheses have been confirmed. According to structural equation modelling data, fate perception elaborates 17% of variance in farming perception and 12% of variance in religious attitude perception. While farming perception verbalises 31 % of variance in agricultural production problems, religious attitude perception explains 6 % of variance in agricultural production problems. (shrink)

The aim of this research is to examine the relationships between authenticity, subjective happiness, and life satisfaction. The participants were 347 university students. In this study, the Authenticity Scale, the Subjective Happiness Scale, and Satisfaction with Life Scale were used. The relationships between authenticity, subjective happiness and life satisfaction were examined using correlation analysis and Structural Equation Model. In correlation analysis, authentic living was found positively related to subjective happiness. On the other hand, self-alienation, accepting external influence was (...) found negatively correlated to subjective happiness. Besides subjective happiness and life satisfaction have positive relation. Structural Equation Model showed that self-alienation, accepting external influence results in a decrease subjective happiness on life satisfaction whereas rise in authentic living lead to subjective happiness, so subjective happiness also brings life satisfaction. According to standardized beta coefficients, the most significant predictor of subjective happiness was self-alienation. Results were discussed in the light of the related literature. (shrink)

Shane Harwood and Richard Scheines. Learning Linear Causal Structure Equation Models with Genetic Algorithms.

Background: Some patients are stigmatised as difficult patients by healthcare professionals. This phenomenon has great many negative consequences. The behaviours of healthcare professionals towards difficult patients are important. Objective: To explore the behaviours of all healthcare professionals towards difficult patients. Research Design: This study was based on a cross-sectional research design using structural equation modelling. Participants and Research Context: Two hundred and fifty-four healthcare professionals were involved in the study in Turkey. ‘Participant Information Form’ and the ‘Healthcare (...) Professionals Behaviour Assessment Questionnaire For Difficult Patient’ were used to collect data from participants. Ethical Consideration: Ethical approval was obtained from Gazi University Ethics Committee for the study. Informed consent of the participants in the study was taken and the confidentiality of the participants was ensured. Findings: It was explored that the behaviours of healthcare professionals towards difficult patients were categorised into ethical, supportive and negative. The highest mean score was supportive behaviour and the least mean score was negative. According to structural equation modelling, the most important predictor of difficult encounters was an ethical dimension. One-unit increase in ethical behaviour contributed to 0.92 unit increase in positive patient behaviour. Discussion: Patients generally are perceived as ‘difficult patient’ by the healthcare professionals, so the patients’ treatment and care services are affected negatively due to healthcare professionals’ negative beliefs and attitudes. The healthcare professionals should behave supportively towards difficult patients. Conclusion: Healthcare professionals should be aware of management strategies in dealing with difficult encounters. The behaviours of healthcare professionals should be improved in a positive way and awareness of ethical dimension of difficult encounters should be increased. (shrink)

Linear structural equation models (SEMs) are widely used in sociology, econometrics, biology, and other sciences. A SEM (without free parameters) has two parts: a probability distribution (in the Normal case specified by a set of linear structural equations and a covariance matrix among the “error” or “disturbance” terms), and an associated path diagram corresponding to the functional composition of variables specified by the structural equations and the correlations among the error terms. It is often thought that (...) the path diagram is nothing more than a heuristic device for illustrating the assumptions of the model. However, in this paper, we will show how path diagrams can be used to solve a number of important problems in structural equation modelling. (shrink)

Intra-organization and inter-organization collaboration and governance are becoming increasingly important for megaprojects. Different stakeholders form intricate links in a network structure. This study explores the role and effect of hybrid governance on complex network projects, such as urban rail transit projects. This included conducting a questionnaire survey with 116 professionals from organizations involved in urban rail transit projects and adopting structural equation modelling to analyze the data. The results analyzed the levels of intra-organization and inter-organization trust under (...) the conditions of power asymmetry and power sharing. A higher level of power asymmetry was associated with lower hybrid governance performance. In contrast, a higher level of power sharing is associated with better hybrid governance performance. The results are generalizable to other projects with complicated organizational and network relationships. (shrink)

Microgames are rapidly gaining increased attention and are highly being considered because of the technology-based media that enhances students’ learning interests and educational activities. Therefore, this study aims to develop a new construct through confirmatory factor analysis, to comprehensively understand the factors influencing the use of microgames in mathematics class. Participants of the study were the secondary school teachers in West Java, Indonesia, which had a 1-year training in microgames development. We applied a quantitative approach to collect the data via (...) online questionnaires through google form. Structural Equation Modelling with AMOS software was used to analyze the proposed model. Empirical results confirmed the perceived easy to use and subjective norm influence relationship with teachers’ microgame usage behaviors and intentions. In this condition, SN was found to have the initial significant influence on behavioral intention, as attitude, BI, and facilitating conditions also correlated with the actual use of microgames. Furthermore, the largest influential factor was BI, with the results subsequently showing that TPACK had no significant influence on the actual use of microgames. This report is expected to help bridge the gap across several previous studies, as well as contribute to the explanation and prediction of the factors influencing the teachers’ mathematical utilization of the study’s program. Besides this, it also helps to increase the use of microgames in teaching and learning activities. (shrink)

The Gibbs sampler can be used to obtain samples of arbitrary size from the posterior distribution over the parameters of a structural equation model (SEM) given covariance data and a prior distribution over the parameters. Point estimates, standard deviations and interval estimates for the parameters can be computed from these samples. If the prior distribution over the parameters is uninformative, the posterior is proportional to the likelihood, and asymptotically the inferences based on the Gibbs sample are the same (...) as those based on the maximum likelihood solution, e.g., output from LISREL or EQS. In small samples, however, the likelihood surface is not Gaussian and in some cases contains local maxima. Nevertheless, the Gibbs sample comes from the correct posterior distribution over the parameters regardless of the sample size and the shape of the likelihood surface. With an informative prior distribution over the parameters, the posterior can be used to make inferences about the parameters of underidentified models, as we illustrate on a simple errors-in-variables model. (shrink)

Recursive linear structural equation models can be represented by directed acyclic graphs. When represented in this way, they satisfy the Markov Condition. Hence it is possible to use the graphical d-separation to determine what conditional independence relations are entailed by a given linear structural equation model. I prove in this paper that it is also possible to use the graphical d-separation applied to a cyclic graph to determine what conditional independence relations are entailed to hold by (...) a given non-recursive linear structural equation model. I also give a causal intepretation to the linear coefficients in a non- recursive structural equation models, and explore the relationships between cyclic graphs and undirected graphs, directed acyclic graphs with latent variables, and chain independence graphs. (shrink)

The presence of agriculture is diminishing in today’s society: it provides only a small percentage of jobs, and the number of visible farms that can provide exposure to agricultural processes is continuously decreasing. We hypothesize that the direct involvement with farm activities or interaction with farmers and visual appreciation of agricultural processes of all kinds, influences rural inhabitants’ relationship to agriculture. We assume that the latter plays a role in how far inhabitants are attached to their place, and more specifically, (...) perceive rural place. In this paper, we aim to initiate a discussion on this complex social relationship and suggest a model to capture fine interactions between relationship to agriculture and rural place attachment. We examine the direct and indirect effects from the density of resident farmers on these interactions. We set up a model using data from empirical research in Germany conducted in 2016. We surveyed rural inhabitants and interviewed farmers in villages purposefully sampled based on high and low density of resident farmers. To reveal underlying relationships among the latent constructs and more directly measurable indicators, as well as the indirect effect of farm presence on place attachment through its effect on forming perceptions about agriculture, we operationalized our analysis using a structural equation model. Besides a good model fit, our initial results indicate that rural inhabitants form stronger relationship to agriculture when the density of resident farmers is higher. Further, farm presence and attachment to rural place are positively related, but needs to be better captured. (shrink)

Bike sharing, as an innovative travel mode featured by mobile internet and sharing, offers a new transport mode for short trips and has a huge positive impact on urban transportation and environmental protection. However, bike-sharing operators face some operational challenges, especially in sustainable development and profitability. Studies show that the customers’ willingness to pay is a key factor affecting bike-sharing companies’ operating conditions. Based on the theories of perceived value, this study conducts an empirical analysis of factors that affect bike-sharing (...) users’ willingness to pay for bike-sharing through measurement scales, user surveys, and structural equation models. We designed a five-point Likert-type scale containing 11 latent variables affecting willingness to pay and a total of 34 measurement items. We investigate bike-sharing users in China’s first and second-tier cities, with a total of 502 participants. The results show that perceived value, payment awareness, trust, and environmental awareness constitute key factors that directly affect bike-sharing users’ willingness to pay. And perceived usefulness, perceived ease-of-use, perceived cost, and perceived risk indirectly affect bike-sharing users’ willingness to pay. However, we found no significant effects of perceived entertainment on perceived value or word of mouth on willingness to pay. Our results are expected to provide theoretical and practical implications for bike-sharing programs. (shrink)

Conventionally, multilevel analysis of covariance (ML-ANCOVA) has been the recommended approach for analyzing treatment effects in quasi-experimental multilevel designs with treatment application at the cluster-level. In this paper, we introduce the generalized ML-ANCOVA with linear effect functions that identifies average and conditional treatment effects in the presence of treatment-covariate interactions. We show how the generalized ML-ANCOVA model can be estimated with multigroup multilevel structural equation models that offer considerable advantages compared to traditional ML-ANCOVA. The proposed model takes into (...) account measurement error in the covariates, sampling error in contextual covariates, treatment-covariate interactions, and stochastic predictors. We illustrate the implementation of ML-ANCOVA with an example from educational effectiveness research where we estimate average and conditional effects of early transition to secondary schooling on reading comprehension. (shrink)

We report a Monte Carlo study examining the effects of two strategies for handling measurement non-invariance – modeling and ignoring non-invariant items – on structural regression coefficients between latent variables measured with item response theory models for categorical indicators. These strategies were examined across four levels and three types of non-invariance – non-invariant loadings, non-invariant thresholds, and combined non-invariance on loadings and thresholds – in simple, partial, mediated and moderated regression models where the non-invariant latent variable occupied predictor, mediator, (...) and criterion positions in the structural regression models. When non-invariance is ignored in the latent predictor, the focal group regression parameters are biased in the opposite direction to the difference in loadings and thresholds relative to the referent group (i.e., lower loadings and thresholds for the focal group lead to overestimated regression parameters). With criterion non-invariance, the focal group regression parameters are biased in the same direction as the difference in loadings and thresholds relative to the referent group. While unacceptable levels of parameter bias were confined to the focal group, bias occurred at considerably lower levels of ignored non-invariance than was previously recognized in referent and focal groups. (shrink)

Numerous studies have shed some light on the importance of associated factors of collaborative attitudes. However, most previous studies aimed to explore the influence of these factors in isolation. With the strategy of data-driven decision making, the current study applied two data mining methods to elucidate the most significant factors of students' attitudes toward collaboration and group students to draw a concise model, which is beneficial for educators to focus on key factors and make effective interventions at a lower cost. (...) Structural equation model trees and structural equation model forests were applied to the Program for International Student Assessment 2015 dataset. By establishing the most important predictors and the splitting rules, these methods constructed multigroup common factor models of collaborative attitudes. The SEM trees showed that home educational resources, home possessions, mother's education, and gender were the most important predictors among the demographic variables, drawing a 5-group model. Among all the predictors, achievement motivation and sense of belonging at school were the most important, drawing a 6-group model. The SEM forest findings proved the relative importance of these variables. This paper discusses various interpretations of these results and their implications for educators to formulate corresponding interventions. Methodologically, this research provides a data mining approach to discover important information from large-scale educational data, which might be a complementary approach to enhance data-driven decision making in education. (shrink)

Structural equation model is a multivariate statistical analysis method. It can not only test some unpredictable abstract ideas, but also design parameters for the causal connection model between independent variables and dependent variables. Among them, the analysis of various latent variables is based on the verification factor analysis technology. The research first collects various relevant data, derives the latent variables and measurement variables, then composes the measurement model, and then verifies the adaptability of the measurement model structure mode (...) through actual data collection. When such suitable factors are determined, a causal model based on path analysis technology for latent variables, that is, a structural model, can be used for parameter design. This article uses the structural equation model as an analysis tool, starting from the three aspects of teachers, cases, and students to evaluate the application effect of the case teaching method in the classroom teaching of intellectual property law course and construct a structural equation model of the influencing factors of the case teaching effect. To understand students’ satisfaction with case teaching effects and related influencing factors, the research results show that the effect of case teaching is jointly affected by the level of teachers, case selection, and student response. Among them, teacher factors have the greatest impact on case teaching effects, followed by case factors, and students have the least. (shrink)

Linear structural equation models (SEMs) are widely used in sociology, econometrics, biology, and other sciences. A SEM (without free parameters) has two parts: a probability distribution (in the Normal case specified by a set of linear structural equations and a covariance matrix among the “error” or “disturbance” terms), and an associated path diagram corresponding to the causal relations among variables specified by the structural equations and the correlations among the error terms. It is often thought that (...) the path diagram is nothing more than a heuristic device for illustrating the assumptions of the model. However, in this paper, we will show how path diagrams can be used to solve a number of important problems in structural equation modelling. (shrink)

BackgroundCOVID-19 break out has created panic and fear in society. A strict kind of lockdown was imposed in Wuhan, Hubei province of China. During home confinement due to lockdown, people face multidimensional issues. The present study explored the psychological impacts of COVID-19 home confinement during the lockdown period and Wuhan’s residents’ attitude toward physical activity.MethodsA cross-sectional online survey was conducted to collect the primary data according to the study objectives. The population was Wuhan residents who were in home confinement. A (...) total of 2280 participant’s reply to the online questionnaire survey and collected data after quantifying the data, about 2200 ; about female, about male, others about, and about were not disclosed their gender participants responses were used for analysis. The collected data were analyzed through appropriate statistical techniques.ResultsAccording to results, H1 is supported with β = −40.793, t = 57.835, p = 0.000, which claimed a negative association between COVID-19 lockdown policy and behavior and attitude. Results for H2 reveals that the COVID-19 lockdown policy have negative influence on emotional control with β = −0.769, t = 46.766, p = 0.000 and it is supported. H3 documented a significant positive relationship between COVID-19 lockdown policy and lockdown period psychological impact, which means lockdown policy, is the main reason to increase the lockdown psychological impact. Further, COVID-19 lockdown policy have negative influence on physical activity and self-belief with β = −0.657, t = 32.766, p = 0.000 and β = −0.620, t = −6.766, p = 0.000 respectively. H6 stated that there is a positive impact of behavior and attitude toward physical activity. The results for H6, behavior, and attitude affecting the physical activity with β = 0.401, t = 10, p = 0.000, which is supported.ConclusionCOVID-19 home confinement created various psychological impacts, negatively affecting the emotional state due to depression and anxiety. Physical activity is the best strategy to manage human nature’s psychological issues, and people’s attitudes were positive toward physical activity during home confinement. However, the lockdown policy also affects physical activity participation negatively, and a sedentary lifestyle prevailed during home confinement. (shrink)

In the past 2 decades latent variable modeling has become a standard tool in the social sciences. In the same time period, traditional linear structural equation models have been extended to include non-linear interaction and quadratic effects (e.g., Klein and Moosbrugger, 2000 ), and multilevel modeling (Rabe-Hesketh et al., 2004 ). We present a general non-linear multilevel structural equation mixture model (GNM-SEMM) that combines recent semiparametric non-linear structural equation models (Kelava and Nagengast, 2012 ; (...) Kelava et al., 2014 ) with multilevel structural equation mixture models (Muthén and Asparouhov, 2009 ) for clustered and non-normally distributed data. The proposed approach allows for semiparametric relationships at the within and at the between levels. We present examples from the educational science to illustrate different submodels from the general framework. (shrink)

BackgroundThere is much overlap among the symptomology of autistic spectrum disorders, obsessive compulsive disorders, and alexithymia, which all typically involve impaired social interactions, repetitive impulsive behaviors, problems with communication, and mental health.AimThis study aimed to identify direct and indirect associations among alexithymia, OCD, cardiac interoception, psychological inflexibility, and self-as-context, with the DV ASD and depression, while controlling for vagal related aging.MethodologyThe data involved electrocardiogram heart rate variability and questionnaire data. In total, 1,089 participant's data of ECG recordings of healthy resting (...) state HRV were recorded and grouped into age categories. In addition to this, another 224 participants completed an online survey that included the following questionnaires: Yale-Brown Obsessive Compulsive Scale ; Toronto Alexithymia Scale 20 ; Acceptance and Action Questionnaire ; Depression, Anxiety, and Stress Scale 21 ; Multi-dimensional Assessment of Interoceptive Awareness Scale ; and the Self-as-Context Scale.ResultsHeart rate variability was shown to decrease with age when controlling for BMI and gender. In the two SEMs produced, it was found that OCD and alexithymia were causally associated with autism and depression indirectly through psychological inflexibility, SAC, and ISen interoception.ConclusionThe results are discussed in relation to the limitations of the DSM with its categorical focus of protocols for syndromes and provide support for more flexible ideographic approaches in diagnosing and treating mental health and autism within the Extended Evolutionary Meta-Model. Graph theory approaches are discussed in their capacity to depict the processes of change potentially even at the level of the relational frame. (shrink)

Complexity has emerged as the new norm in the 21st century, and IS projects play a significant role in organisations to address various socio-political concerns. The purpose of this paper is to understand what are the relevant constructs for measuring IS project complexity. A model for measuring IS project complexity is developed using PLS-SEM. The model reveals that organisational complexity, technical complexity, and uncertainty underpin IS project complexity. Organisational complexity in terms of project team, stakeholder management, and strategic drive should (...) be managed by the project manager. Technical complexity was established in terms of project goals, requirements management, technology management, and norms and standards. Uncertainty in IS projects exists in terms of skills management, the triple constraint, and activity management. Suggestions were provided to guide IS project managers on how to manage each construct and alleviate the level of project complexity. This paper presents an updated and different perspective on measuring and managing IS project complexity. The findings would serve as additional building blocks to further elucidate IS project complexity understanding and assist with improving the value of these projects. Furthermore, the suggestions for IS project managers can lead discussions around how IS projects should be managed to ensure complexity is under control. (shrink)

Background: Forgiveness has the potential to resolve painful feelings arising from nurse–patient conflicts. It would be useful to evaluate direct and indirect important factors which are related to forgiveness in order to design interventions that try to facilitate forgiveness. Aim/objective: The purpose of this study was to evaluate the intermediating role of empathy in the cultural competence–forgiveness association among nurses using structural equation modeling. Research design: The research applied a cross-sectional correlational design. Participants and research context: The study (...) included 380 nurses eight hospitals in southern Iran. Ethical considerations: The Ethics and Research Committee of Birjand University of Medical Sciences approved the study protocol. The voluntary nature of participation was explained consent was obtained from participants, and anonymity was guaranteed. Findings: Most of the participants were married and female and fell in the 20- to 30-year-old category. Most of them (89.5%) had a working experience of 1–10 years. The proposed model showed that nurses’ empathy intermediated the association between nurses’ cultural competence and forgiveness which has fitted the data acceptably (root mean square error approximation = 0.070; comparative fit index = 0.993; goodness-of-fit index = 0.983; and χ2/df = 2.85). Conclusion: Empathy skills and cultural competence training were essential for interventions aimed at increasing the tendency to forgive patients. In such interventions, planners should aim at increasing nurses’ cultural competence in order to enhance their empathy toward patients, which can, in turn, lead to a greater wish to forgive patients. (shrink)

Structural equations have become increasingly popular in recent years as tools for understanding causation. But standard structural equations approaches to causation face deep problems. The most philosophically interesting of these consists in their failure to incorporate a distinction between default states of an object or system, and deviations therefrom. Exploring this problem, and how to fix it, helps to illuminate the central role this distinction plays in our causal thinking.

This cross-sectional study aimed to assess the applicability of social cognitive determinants among the Chinese adolescents and examine whether the predictability of the social cognitive theory model on physical activity differs across gender and urbanization. A total of 3,000 Chinese adolescents ranging between the ages of 12–15 years were randomly selected to complete a set of questionnaires. Structural equation modeling was applied to investigate the relationships between social cognitive variables and PA in the urbanization and gender subgroups. The (...) overall model explained 38.9% of the variance in PA. Fit indices indicated that the structural model of SCT was good: root mean square error of approximation = 0.047, RMR = 0.028, goodness of fit index = 0.974, adjusted goodness of fit index = 0.960, Tucker–Lewis coefficient = 0.971, and comparative fit index = 0.978. Regarding the subgroup analysis, social support had a more substantial impact on the PA of adolescents in suburban areas than that in urban areas, whereas self-regulation had a more substantial impact on the PA of adolescents in urban areas than in suburban areas. The results indicate that the SCT model predicts the PA of Chinese adolescents substantially. An SCT model could apply over a range of subgroups to predict the PA behavior and should be considered comprehensively when designing interventions. These findings would benefit PA among the Chinese adolescents, especially across genders and urbanization. (shrink)

Hall [(2007), Philosophical Studies, 132, 109–136] offers a critique of structural equations accounts of actual causation, and then offers a new theory of his own. In this paper, I respond to Hall’s critique, and present some counterexamples to his new theory. These counterexamples are then diagnosed.

Saving money benefits individuals and the economy. This research examines the factors affecting Malaysian military personnel's saving habits. The study focuses on the impact of financial literacy, financial inclusions, financial stress, peer influence, military culture, and self-discipline on saving habits. The positivist study design was based on a survey questionnaire of 1000 Malaysian Armed Forces military personnel. Data from the pilot and main survey were analysed using SPSS 29.0 and SmartPLS4, respectively. The study randomly selected respondents from a population of (...) approximately 120,000 actively serving military personnel. The respondents include officers and other ranks deployed at various military bases and camps in Malaysia. Except for self-control, financial stress, and financial inclusions, the remaining three variables have strong connections with the savings habit. The findings support life cycle and planned behaviour theories. This study sheds light on military personnel and the necessity of savings strategies for financial readiness. (shrink)

This study empirically examined the effects of ethical leadership and ethical climate on employee ethical behavior in the international port context using survey data collected from 128 respondents who worked in Taiwan International Ports Corporation in Taiwan. Research hypotheses were formulated from the previous literature and tested using structural equation modeling. Results indicated that ethical leadership had a significant impact on ethical climate and the ethical behavior of TIPC employees. Ethical climate was found to be positively associated with (...) employee ethical behavior. The theoretical and practical implications of the research findings are discussed. (shrink)

The phenomenon of knowledge withholding is a vital issue that undermines knowledge sharing and innovation, hinders the development of offline and online organizations. Clarifying the relationship between influencing factors and knowledge withholding is significant to improve the phenomenon of knowledge withholding in offline and online organizations. Few types of research focus on the online virtual academic community and integrate the three factors of knowledge, individual, and environment to research knowledge withholding. To solve the limitation, this research is based on sociology (...) and psychology-related theories. The two dimensions of enabling and inhibition are divided into factors affecting knowledge withholding. An attempt is made to explore the path between the three types of factors influencing knowledge, individual and environment, and knowledge withholding. This study collected data from 616 users in China’s virtual academic community. It used a structural equation model combined with a cross-layer connected neural network to conduct an empirical analysis on the proposed hypothesis. The results found that: in the virtual academic community, knowledge power in the enabling dimension is the main reason for users to form knowledge psychological ownership, which affects users’ knowledge withholding. However, the effect of professional commitment on users’ knowledge psychological ownership is not significant. After SEM-ANN model fitting, the combined inhibitory effect of community privacy protection and community reciprocity on user knowledge withholding in the inhibition dimension is significantly improved. This research has a specific guiding significance for enhancing the knowledge withholding phenomenon of the virtual academic community and creating an excellent academic exchange atmosphere. (shrink)

In classifications of vocabulary knowledge, vocabulary size and depth have often been separately conceptualized (Schmitt, 2014). Although size and depth are known to be substantially correlated, it is not clear whether they are a single construct or two separate components of vocabulary knowledge (Yanagisawa & Webb, 2020). This issue has not been addressed extensively in the literature and can be better examined using structural equation modeling (SEM), with measurement error modeled separately from the construct of interest. The current (...) study reports on conventional and Bayesian SEM approaches (e.g., Muthén & Asparouhov, 2012) to examine the factor structure of the size and depth of second language vocabulary knowledge of Japanese adult learners of English. A total of 255 participants took five vocabulary tests. One test was designed to measure vocabulary size in terms of the number of words known, while the remaining four were designed to measure vocabulary depth in terms of word association, polysemy, and collocation. All tests used a multiple-choice format. The size test was divided into three subtests according to word frequency. Results from conventional and Bayesian SEM show that a correlated two-factor model of size and depth with three and four indicators, respectively, fit better than a single-factor model of size and depth. In the two-factor model, vocabulary size and depth were strongly correlated (r =.945 for conventional SEM and.943 for Bayesian SEM with cross loadings), but they were distinct. The implications of these findings are discussed. (shrink)

Recent accounts of actual causation are stated in terms of extended causal models. These extended causal models contain two elements representing two seemingly distinct modalities. The first element are structural equations which represent the or mechanisms of the model, just as ordinary causal models do. The second element are ranking functions which represent normality or typicality. The aim of this paper is to show that these two modalities can be unified. I do so by formulating two constraints under which (...) extended causal models with their two modalities can be subsumed under so called which contain just one modality. These two constraints will be formally precise versions of Lewissystem of weights or priorities” governing overall similarity between possible worlds. (shrink)

This article briefly review the fundamentals of structural equation modeling for readers unfamiliar with the technique then goes on to offer a review of the Martin and Cullen paper. In summary, a number of fit indices reported by the authors reveal that the data do not fit their theoretical model and thus the conclusion of the authors that the model was “promising” are unwarranted.

This study explores how the perceived co-creation values from tourists’ perspectives are applied in the customized tour arrangement service setting. The sequential qualitative and quantitative methods are adopted for this study. The initial qualitative method in terms of the proactive semi-structured interview is conducted to identify and explore the dimension of the PCV construct and to develop its measurement scale. The quantitative method by the structure equation model is employed for the proposed conceptual model fitness assessment and consolidation. Our (...) work contributes to the progression of value co-creation research in a customized tourism context and provides a valid and reliable PCV instrument to tourism practitioners for a better service platform designing. The mediating role of customer satisfaction between PCV and customer loyalty offers service providers a deeper understanding of customer psychology and behavior, and thus, the loyal customer cultivation strategy. (shrink)

Background: This study examined the cyberbullying experience and coping manners of adolescents in urban Vietnam and explored the mediating effect of different support to the associations between cyberbullying and mental health issues.Methods: A cross-sectional study was performed on 484 students at four secondary schools. Cyberbullying experience, coping strategies, psychological problems, and family, peer, and teacher support were obtained. Structural equation modeling was utilized to determine the mediating effects of different support on associations between cyberbullying and psychological problems.Results: There (...) were 11.6 and 28.3% of students who reported that they experienced and observed at least one cyberbullying act in the last 3 months, respectively. Among the victims, only 48.2% tried to stop the perpetrators. Meanwhile, the majority of observers belonged to the “Intervene” group who tried to report cyberbullying acts or help victims. Family support was found to partially mediate associations between cyberbullying experience and observation with levels of psychological problems among adolescents.Conclusion: The 3-month rate of cyberbullying experience and observation among urban adolescents aged 11–14 was low. However, current coping strategies against cyberbullying were not sufficient. Family support is an important factor that should be considered for designing interventions to mitigating the impacts of cyberbullying on the mental health of adolescents. (shrink)

Social responsibility is addressed to corporations, but can also be applied to other powerful organizations. This study tests the impact of labor union social responsibility on key measures of labor union attachment. After developing a scale of labor union social responsibility, craft union apprentice workers were surveyed and their responses analyzed with structural equation modeling. Labor union social responsibility was directly and positively related to union commitment and job satisfaction. Union commitment and job satisfaction fully mediated the negative (...) relationship between labor union social responsibility and propensity to withdraw from the union, and the positive relationship between labor union social responsibility and union participation. The results suggest that labor union social responsibility can enhance union attachment and inform union strategy. (shrink)

An important factor that leads governments to engage in public service contracts with nonprofit organizations is the belief that they share similar ethical and value orientations that will allow governments to reduce monitoring costs. However the notion of the existence of similarities in ethical climate has not been systematically examined. The purpose of this paper is to investigate the ethical climate in government and nonprofit sectors and to determine the extent to which similarities (and differences) exist in ethical climate dimensions. (...) Using survey data and structural equation modeling technique, the factor structure equivalence and measurement invariance of the ethical climate in the two sectors are tested. Results indicate that while there is a significant overlap in shared perception of ethical climate dimensions, there are also key differences between the two sectors. The outcome of this research provides important preliminary insights for public policy makers in government to better understand the implications of using the nonprofit sector for service delivery. (shrink)

The paper discusses from a metaphysical standpoint the nature of the dependence relation underpinning the talk of mutual action between material and spatiotemporal structures in general relativity. It is shown that the standard analyses of dependence in terms of causation or grounding are ill-suited for the general relativistic context. Instead, a non-standard analytical framework in terms of structural equation modeling is exploited, which leads to the conclusion that the kind of dependence encoded in the Einstein field equations is (...) a novel one. (shrink)

Teacher self-efficacy is one of the most critical factors influencing Students’ learning outcomes. Studies have shown that teacher-perceived principal leadership, teacher collaboration, and teaching experience are the critical factor that affects teacher self-efficacy. However, little is known about the mechanisms behind this relationship. This study examined whether teacher collaboration would mediate the relationship between teacher-perceived principal leadership and teacher self-efficacy, and the moderating role of teaching experience in the mediating process. With an analysis of a dataset from 14,121 middle school (...) teachers in China, this study first testified to the positive role that teacher-perceived principal leadership played in teacher self-efficacy. Furthermore, it revealed that teacher collaboration mediates this relationship and the mediated path was moderated by teaching experience. Finally, it also indicated that the threshold of teaching experience linking the teacher-perceived leadership with teacher self-efficacy was approximately in the third year, and their relationship was stronger when teaching experience was below the threshold. This study highlighted the mediating and moderating mechanisms linking the teacher-perceived principal leadership and teacher self-efficacy, which has important theoretical and practical implications for intervention and enhancement of teacher self-efficacy. (shrink)