Bayesian Confirmatory Factor Analysis Research Articles

Evaluating Cronbach’s Coefficient Alpha and Testing Its Identity to Scale Reliability: A Direct Bayesian Confirmatory Factor Analysis Procedure

ABSTRACT A Bayesian statistics-based approach is discussed that can be used for direct evaluation of the popular Cronbach’s coefficient alpha as an internal consistency index for multiple-component measuring instruments, as well as for testing its identity to scale reliability. The method represents an application of confirmatory factor analysis within the Bayesian inference framework and is widely applicable in empirical measurement research using popular latent variable modeling software. The procedure readily furnishes posterior median point estimates and credible intervals of coefficient alpha. The approach also permits testing a necessary and sufficient condition for population equality of the alpha and scale reliability coefficients, and under its plausibility provides in addition a dependable means for estimation of instrument reliability. The outlined procedure is illustrated using numerical data.

Association of latent factors of neuroinflammation with Alzheimer's disease pathology and longitudinal cognitive decline.

We investigated the association of inflammatory mechanisms with markers of Alzheimer's disease (AD) pathology and rates of cognitive decline in the AD spectrum. We studied 296 cases from the Deutsches Zentrum für Neurodegenerative Erkrankungen Longitudinal Cognitive Impairment and Dementia Study (DELCODE) cohort, and an extension cohort of 276 cases of the Alzheimer's Disease Neuroimaging Initiative study. Using Bayesian confirmatory factor analysis, we constructed latent factors for synaptic integrity, microglia, cerebrovascular endothelial function, cytokine/chemokine, and complement components of the inflammatory response using a set of inflammatory markers in cerebrospinal fluid. We found strong evidence for an association of synaptic integrity, microglia response, and cerebrovascular endothelial function with a latent factor of AD pathology and with rates of cognitive decline. We found evidence against an association of complement and cytokine/chemokine factors with AD pathology and rates of cognitive decline. Latent factors provided access to directly unobservable components of the neuroinflammatory response and their association with AD pathology and cognitive decline.

Anxiety in response to the climate and environmental crises: validation of the Hogg Eco-Anxiety Scale in Germany.

As the climate and environmental crises unfold, eco-anxiety, defined as anxiety about the crises' devastating consequences for life on earth, affects mental health worldwide. Despite its importance, research on eco-anxiety is currently limited by a lack of validated assessment instruments available in different languages. Recently, Hogg and colleagues proposed a multidimensional approach to assess eco-anxiety. Here, we aim to translate the original English Hogg Eco-Anxiety Scale (HEAS) into German and to assess its reliability and validity in a German sample. Following the TRAPD (translation, review, adjudication, pre-test, documentation) approach, we translated the original English scale into German. In total, 486 participants completed the German HEAS. We used Bayesian confirmatory factor analysis (CFA) to assess whether the four-factorial model of the original English version could be replicated in the German sample. Furthermore, associations with a variety of emotional reactions towards the climate crisis, general depression, anxiety, and stress were investigated. The German HEAS was internally consistent (Cronbach's alphas 0.71-0.86) and the Bayesian CFA showed that model fit was best for the four-factorial model, comparable to the factorial structure of the original English scale (affective symptoms, rumination, behavioral symptoms, anxiety about personal impact). Weak to moderate associations were found with negative emotional reactions towards the climate crisis and with general depression, anxiety, and stress. Our results support the original four-factorial model of the scale and indicate that the German HEAS is a reliable and valid scale to assess eco-anxiety in German speaking populations.

Evaluating the Feasibility of Emotion Expressions in Avatars Created From Real Person Photos: Pilot Web-Based Survey of Virtual Reality Software.

The availability and potential of virtual reality (VR) has led to an increase of its application. VR is suggested to be helpful in training elements of social competence but with an emphasis on interventions being tailored. Recognizing facial expressions is an important social skill and thus a target for training. Using VR in training these skills could have advantages over desktop alternatives. Children with autism, for instance, appear to prefer avatars over real images when assessing facial expressions. Available software provides the opportunity to transform profile pictures into avatars, thereby giving the possibility of tailoring according to an individual's own environment. However, the emotions provided by such software should be validated before application. Our aim was to investigate whether available software is a quick, easy, and viable way of providing emotion expressions in avatars transformed from real images. A total of 401 participants from a general population completed a survey on the web containing 27 different images of avatars transformed, using a software, from real images. We calculated the reliability of each image and their level of difficulty using a structural equation modeling approach. We used Bayesian confirmatory factor analysis testing under a multidimensional first-order correlated factor structure where faces showing the same emotions represented a latent variable. Few emotions were correctly perceived and rated as higher than other emotions. The factor loadings indicating the discrimination of the image were around 0.7, which means 49% shared variance with the latent factor that the face is linked with. The standardized thresholds indicating the difficulty level of the images are mostly around average, and the highest correlation is between faces showing happiness and anger. Only using a software to transform profile pictures to avatars is not sufficient to provide valid emotion expressions. Adjustments are needed to increase faces' discrimination (eg, increasing reliabilities). The faces showed average levels of difficulty, meaning that they are neither very difficult nor very easy to perceive, which fits a general population. Adjustments should be made for specific populations and when applying this technology in clinical practice.

Operator Control Room Risk-taking Questionnaire (ORTQ): A Specific Risk-taking Assessment Tool Validated in Iranian Workers

Background: Risk-taking has an influential role in accident occurrence or prevention. Hence, having a valid tool to evaluate workers for risk-taking is necessary. Risk-taking has been intensely studied in the field of psychology and neuroscience, leading to the development of several questionnaires and software. Objectives: In the present study, a new questionnaire was developed and validated based on the conceptual model to assess risk-taking behavior in people working in operator control rooms in industrial settings. Methods: Questions were selected from well-known psychological scales based on a conceptual model, followed by approving its face validity and conducting exploratory factor analysis (EFA). Afterward, some models were computed with confirmatory factor analysis (CFA) and Bayesian structural equation modeling (BSEM). The questionnaire was completed by 208 males who worked in the control room of some industries in Markazi province, Iran, in 2021. Test-retest reliability was done by 42 participants at a three-month interval. Results: One factor and 12 items were suggested by EFA. The model was accepted based on the results of Operator Control Room Risk-taking Questionnaire (ORTQ) goodness of fit CFA (χ2/df = 1.89, comparative fit index (CFI) = 0.90, root mean square error of approximation (RMSEA) = 0.09, and P < 0.001). The correlation coefficient (P < 0.001) between risk-taking and impulsivity was 0.65. However, it was 0.69 between venturesomeness and risk-taking and 0.58 between impulsivity and venturesomeness. Cronbach's alpha was 0.89 for ORTQ test-retest reliability. Operator Control Room Risk-taking Questionnaire was confirmed to have a better leave-one-out cross-validation information criterion (LOOIC) based on BSEM rather than Bayesian confirmatory factor analysis (BCFA). Conclusions: Operator Control Room Risk-taking Questionnaire is a valid and reliable questionnaire that can be used as a screening tool for risk-taking traits in workers before enrolment.

Preliminary validation of a brief PROM assessing psychological distress in patients with malignant mesothelioma: The mesothelioma psychological distress tool-Patients.

Psychological suffering in malignant mesothelioma (MM) differs from that in other cancers because of its occupational etiology, and we aimed to develop specific patient-reported outcome measures to assess it. We used a multi-method prospective observational multicentric study (N = 149), and a preliminary questionnaire validation was performed through a Bayesian approach. Item analysis showed a good internal consistency and reliability (Cronbach alpha = 0.79 [95% CI = 0.74-0.93]. Twenty of the 41 initial items were selected as posterior 95% highest density interval factor loading standardized effect size fell outside of the region of practical equivalence. Bayesian exploratory factor analysis showed a two-factor structure: (1) Trauma-related reactions (TR, 13 items) and (2) Claim for justice (CJ, 7 items), confirmed by the Bayesian confirmatory factor analysis. Latent factors were poorly correlated (Posterior median: 0.13; 95% CI = -0.079 to 0.323). The 90% root mean square error of approximation posterior median was 0.04 [90% CI = 0.03-0.58]; the 90% chi-square posterior median was 242 [90% CI = 209-287]. Psychological suffering in MM patients implies negative cognitive, emotional, and somatic reactions related to the traumatic impact of the disease and the need to obtain justice through economic compensation. Our findings provide preliminary evidence that the Mesothelioma Psychological Distress Tool-Patients could be a promising and reliable instrument to assess MM patients' psychological distress.

Impact of Informative Priors on Model Fit Indices in Bayesian Confirmatory Factor Analysis

Assessing model fit is a key component of structural equation modeling (SEM); however, measures of fit in Bayesian SEM remain limited. Recently, versions of frequentist fit indices have been adapted for use in Bayesian models, but the impact of prior information on these fit indices remains unknown. This simulation study investigates the performance of three fit indices (RMSEA, CFI, and TLI) in Bayesian confirmatory factor analysis (CFA) across a variety of prior specifications that included different degrees of informativeness and inaccuracy. Results show that Bayesian fit indices are impacted by prior choice, particularly when sample sizes are small. We discuss implications of assessing model fit with Bayesian fit indices and provide recommendations for applied researchers.

Applications of Bayesian Confirmatory Factor Analysis in Behavioral Measurement: Strong Convergence of a Bayesian Parameter Estimator

ABSTRACT This article is concerned with the large-sample parameter estimatorbehavior in applications of Bayesian confirmatory factor analysis in behavioral measurement. The property of strong convergence of the popular Bayesian posterior median estimator is discussed, which states numerical convergence with probability 1 of the resulting estimates to the population parameter value as sample size increases without bound. This property is stronger than the consistency and convergence in distribution of that estimator, which have been commonly referred to in the literature. A numerical example is utilized to illustrate this almost sure convergence of a Bayesian latent correlation estimator. The paper contributes to the body of research on optimal statistical features of Bayesian estimates and concludes with a discussion of the implications of this large-sample property of the Bayesian median estimator for empirical measurement studies.

The Sensory Classroom Teacher Questionnaire: A tool for assessing conducive classroom conditions for children with ADHD

Physical classrooms provide immense sensory stimulation to children and inform behaviour, cognitive processes and psychological state of mind. Children diagnosed with any subtype of attention-deficit hyperactivity disorder (ADHD) are more likely to exhibit sensory integration/processing impairments that contribute to inappropriate behavioural and learning responses. Teachers need good information and user-friendly psycho-educational instruments to meet the needs of children diagnosed with any ADHD subtype. The Sensory Classroom Teacher Questionnaire (SCTQ) utilises ADHD symptomatology to evaluate learning spaces that support children in regulating their response to sensory input. We report on the piloted design and refinement of the SCTQ based on best practices. A convenience sample of South African early childhood teachers administered the first (n = 313) and second (n = 72) versions of the SCTQ at various primary schools. Cross-disciplinary specialists appraised the SCTQ for content validity, while the Rasch rating scale model was applied to assess internal construct reliability and validity. The structure of the latent constructs was assessed using Bayesian confirmatory factor analysis. Following the first pilot, we refined the SCTQ by combining or deleting unnecessary items and reducing the five-point Likert scale to a three-point scale. Revising the Likert scale in version one was necessary to improve category functioning. Adjusting the three-point scale in the revised SCTQ indicated good item and scale functioning. We show the conceptual framework, refinement process, all results and the most recent version of the SCTQ for teachers to use and educational researchers to adapt further.

A Model Comparison Approach to Posterior Predictive Model Checks in Bayesian Confirmatory Factor Analysis

ABSTRACT Posterior Predictive Model Checking (PPMC) is frequently used for model fit evaluation in Bayesian Confirmatory Factor Analysis (BCFA). In standard PPMC procedures, model misfit is quantified by comparing the location of an ML-based point estimate to the predictive distribution of a statistic. When the point estimate is far from the center posterior predictive distribution, model fit is poor. Not included in this approach, however, is the variability of the Maximum Likelihood (ML)-based point estimates. We propose a new method of PPMC based on comparing posterior predictive distributions of a hypothesized and saturated BCFA model. The method uses the predictive distribution of the saturated model as a reference and the Kolmogorov-Smirnov (KS) statistic to quantify the local misfit of hypothesized models. The results of the simulation study suggest that the saturated model PPMC approach was an accurate method of determining local model misfit and could be used for model comparison. A real data example is also provided in this study.

Modelling variance in the multidimensional Health Literacy Questionnaire: Does a General Health Literacy factor account for observed interscale correlations?

Objectives:Self-report measures of health literacy frequently encompass a group of conceptually distinct but related domains scored as either a single scale or separately for each domain. Psychometric studies of the 44-item Health Literacy Questionnaire, scored as nine separate scales, typically report the results of correlated factors confirmatory factor analyses as validity evidence. However, some scales are quite strongly correlated, raising the question of whether there is sufficient discriminant validity to warrant separate scoring. This psychometric study aims to contrast the results of fitting higher-order and bifactor models as alternative options to illuminate the issue.Methods:Correlated factors, higher-order and bifactor confirmatory factor analysis models were fitted to an Australian sample of responses to the Health Literacy Questionnaire (N = 813) using Bayesian confirmatory factor analysis methods.Results:All models representing a nine-factor structure for the Health Literacy Questionnaire fitted well. The correlated factors model replicated previous findings, showing inter-factor correlations between 0.19 and 0.93. A higher-order model showed relatively high loadings of all nine first-order factors on the second-order factor with particularly high loadings (⩾0.97) for three. Two bifactor models showed that the majority of Health Literacy Questionnaire items were multifactorial, each containing systematic variance from both a General Health Literacy factor and a domain-specific factor. Seven items from four scales were identified as strongly associated with the General Health Literacy factor, with item content suggesting that this factor indexes a broad sense of agency and efficacy in interacting with health-related information and healthcare providers.Conclusion:Contrasting correlated factors, higher-order and bifactor models fitted to the Health Literacy Questionnaire suggest that constituent items in self-report health literacy questionnaires might be anticipated to represent at least two sources of reliable and substantive common factor variance: variance associated with General Health Literacy and variance associated with a more specific domain, suggesting that items may be ‘irreducibly’ heterogeneous. Implications for test development and validation practice are discussed.

Psychometric validation of the Partners in Health scale as a self‐management tool in patients with liver cirrhosis

Liver cirrhosis is a chronic disease complicated by recurrent hospital admissions. Self-management skills could facilitate optimal disease management. At present there is no validated instrument for measuring self-management in these patients. Hence, we evaluated the internal reliability and construct validity of the Partners in Health (PIH) scale, a chronic condition self-management tool in cirrhotic patients. In this prospective cohort study, the PIH scale was administered to 133 consenting patients within a Chronic Liver Failure Program of a tertiary hospital from February 2017 to May 2018. A Bayesian confirmatory factor analysis was used to evaluate a priori four-factor structure. Omega coefficients and 95% credible intervals (CrI) were used to assess internal reliability. Known-group validity was assessed in patients receiving active case management (n = 60) versus those without (n = 73). The mean (± standard deviation (SD)) age of the participants was 62 (±11) years. Model fit for the hypothesised model was adequate (posterior predictive P-value=0.073) and all hypothesised factor loadings were substantial (>0.6) and significant (P < 0.001). Omega coefficients (95% CrI) for the PIH subscales of Knowledge, Partnership, Management and Coping were 0.88 (0.82-0.91), 0.68 (0.57-0.76), 0.92 (0.89-0.94) and 0.89 (0.85-0.92) respectively. The mean (±SD) overall PIH score was higher in patients receiving case management compared to those without case management (81 ± 12 vs 73 ± 17, P < 0.001). The dimensionality, known-group validity and reliability of the PIH scale for measuring self-management in patients with liver cirrhosis were confirmed. Its clinical predictive value requires further assessment.

Searching for causal relationships among latent variables concerning performance, carcass, and meat quality traits in broilers.

In causal relationship studies, the latent variables may summarize the phenotypes in theoretical traits according to their phenotypic correlations, improving the understanding of causal relationships between broilers phenotypes. In this study, we aimed to investigate potential causal relationships among latent variables in broilers using a structural equation model in the context of genetic analysis. The data used in this study comprised 14 traits in broilers with 2,017 records each, and 104,154 animals in pedigree. Four latent variables (WEIGHT, LOSSES, COLOUR, and VISCERA) were defined and validated using Bayesian Confirmatory Factor Analysis. Subsequently, a search for causal linkage structures was performed, obtaining a single causal link structure between the latent variables. Then, this information was used to fit the structural equation model (SEM). The results from the SEM indicated positive causal effects of the variables WEIGHT and LOSSES on the variables VISCERA and COLOUR, respectively, with structural coefficient estimates of 1.006 and 0.040, respectively. On the other hand, an antagonist causal effect of the variable WEIGHT on the variable LOSSES was verified, with a structural coefficient estimate of -4.333. These results highlight the causal relationship between performance and meat quality traits, which may be associated with the natural processes involved in the conversion of muscle into meat and the structural changes in muscle tissues due to intense selection for high growth rates in broilers.

Bayesian and Maximum-Likelihood Modeling and Higher-Level Scores of Interpersonal Problems With Circumplex Structure.

Difficulties in interpersonal behavior are often measured by the circumplex-based Inventory of Interpersonal Problems. Its eight scales can be represented by a three-factor structure with two circumplex factors, Dominance and Love, and a general problem factor, Distress. Bayesian confirmatory factor analysis is well-suited to evaluate the higher-level structure of interpersonal problems because circumplex loading priors allow for data-driven adjustments and a more flexible investigation of the ideal circumplex pattern than conventional maximum likelihood confirmatory factor analysis. Using a non-clinical sample from an online questionnaire study (N = 822), we replicated the three-factor structure of the IIP by maximum likelihood and Bayesian confirmatory factor analysis and found great proximity of the Bayesian loadings to perfect circumplexity. We found additional support for the validity of the three-factor model of the IIP by including external criteria-Agreeableness, Extraversion, and Neuroticism from the Big Five and subclinical grandiose narcissism-in the analysis. We also investigated higher-level scores for Dominance, Love, and Distress using traditional regression factor scores and weighted sum scores. We found excellent reliability (with Rtt ≥ 0.90) for Dominance, Love, and Distress for the two scoring methods. We found high congruence of the higher-level scores with the underlying factors and good circumplex properties of the scoring models. The correlational pattern with the external measures was in line with theoretical expectations and similar to the results from the factor analysis. We encourage the use of Bayesian modeling when dealing with circumplex structure and recommend the use of higher-level scores for interpersonal problems as parsimonious, reliable, and valid measures.

Validity and usefulness of the student-athletes' motivation toward sport and academics questionnaire: a Bayesian multilevel approach.

BackgroundReliable assessment and understanding of student-athletes’ motivation for dual careers are crucial to support their career development and transitions. The purpose of this research was to examine the validity and usefulness of the student-athletes’ motivation toward sport and academics questionnaire (SAMSAQ-PT) in the Brazilian higher education context. Four studies were performed.MethodsIn study one, conceptually and semantic translation of the questionnaire and Bayesian exploratory factor analysis were conducted. In study two, a Bayesian confirmatory factor analysis with an independent sample was performed. In study three, Bayesian multilevel modeling was applied to examine the construct validity of the questionnaire in a cross-sectional sample. In study four, the SAMSAQ-PT sensitiveness was examined in a longitudinal sample, and the results were interpreted based on multilevel regression and poststratification.ResultsAltogether the results provided evidence validity and usefulness of the SAMSAQ-PT in Brazilian student-athletes. The Brazilian student-athletes’ motivation scores were sensitive to the influence of sex, sport level, and type of university on career and sport motivation. SAMSAQ-PT estimate scores across an academic year showed a trend of stability in the scores, adjusting for sex, sport level, type of university, and student-athlete status.ConclusionThe SAMSAQ-PT proved to be a robust and valuable questionnaire, which could be used in Portuguese-speaking countries. The findings of the cross-sectional and longitudinal surveys urge to consider individual and contextual characteristics when investigating motivation of dual-career of athletes, also concerning the sex-related opportunities in university sports. Furthermore, there is a need for a call for action to promote and nurture the student-athletes motivation to remain engaged in both sports and educational commitments.

Identifying strategies to improve PANSS based dimensional models in schizophrenia: Accounting for multilevel structure, Bayesian model and clinical staging

BackgroundDimensional approaches can decompose a construct in a set of continuous variables, improving the characterization of complex phenotypes, such as schizophrenia. However, the five-factor model of the Positive and Negative Syndrome Scale (PANSS), the most used instrument in schizophrenia research, yielded poor fits in most confirmatory factor analysis (CFA) studies, raising concerns about its applications. Thus, we aimed to identify dimensional PANSS CFA models with good psychometric properties by comparing the traditional CFA with three methodological approaches: Bayesian CFA, multilevel modeling, and Multiple Indicators Multiple Causes (MIMIC) modeling. MethodsClinical data of 700 schizophrenia patients from four centers were analyzed. We first performed a traditional CFA. Next, we tested the three techniques: 1) a Bayesian CFA; 2) a multilevel analysis using the centers as level; and 3) a MIMIC modeling to evaluate the impact of clinical staging on PANSS factors and items. ResultsCFA and Bayesian CFA produced poor fit models. However, when adding a multilevel structure to the CFA model, a good fit model emerged. MIMIC modeling yielded significant differences in the factor structure between the clinical stages of schizophrenia. Sex, age, age of onset, and duration of illness did not significantly affect the model fit. ConclusionOur comparison of different CFA methods highlights the need for multilevel structure to achieve a good fit model and the potential utility of staging models (rather than the duration of illness) to deal with clinical heterogeneity in schizophrenia. Large prospective samples with biological data should help to understand the interplay between psychometrics concerns and neurobiology research.

Examining the factor structure and its replicability across multiple listening test forms: Validity evidence for the Michigan English Test

This study evaluated the validity of the Michigan English Test (MET) Listening Section by investigating its underlying factor structure and the replicability of its factor structure across multiple test forms. Data from 3255 test takers across four forms of the MET Listening Section were used. To investigate the factor structure, each form was fitted with four Bayesian confirmatory factor analysis (CFA) models: (1) a three correlated-factor model, (2) a bi-factor model, (3) a higher-order factor model, and (4) a single general-factor model. In addition, a four-pronged heuristic comprising construct delineation, construct operationalization, factor structure analysis, and congruence coefficient was developed to examine the replicability of factor structures across the test forms. Results from the CFA models showed that the test forms were unidimensional and the four-pronged heuristic indicated that the test construct was consistently operationalized across forms. Furthermore, the congruence coefficient indicated that the factor structure representing listening was highly similar and replicable across test forms. In sum, the construct of the MET Listening Section did not comprise divisible subskills. Yet, the unidimensional factor structure of the test was replicable across the test forms.

Drop-the-p: Bayesian CFA of the Multidimensional Scale of Perceived Social Support in Australia.

AimWe aimed to investigate whether the 12-item Multidimensional Scale of Perceived Social Support (MSPSS) constitutes a valid and reliable measure of social support for the general adult Australian population.MethodsData were from Australia’s National Survey of Adult Oral Health 2004–2006 and included 3899 participants aged 18 years old and over. The psychometric properties were evaluated with Bayesian confirmatory factor analysis. One-, two-, and three-factor (Significant Other, Family and Friends) structures were tested. Model fit was assessed with the posterior predictive p-value (PPPχ2), Bayesian root mean square error of approximation (BRMSEA), and Bayesian comparative fit index (BCFI). Dimensionality was tested by comparing competing factorial structures with the Bayes factor (BF). Reliability was evaluated with the Bayesian ΩH. Convergent validity was investigated with the Perceived Stress Scale (PSS) and discriminant validity with the Perceived Dental Control scale (PDC-3).ResultsThe theoretical three-factor model (Significant Other, Family, and Friends) provided a good fit to the data [PPPχ2 < 0.001, BRMSEA = 0.089-95% credible interval (CrI) (0.088, 0.089); BCFI = 0.963-95% CrI (0.963, 0.964)]. The BF provided decisive support for the three-factor structure in relation to the other structures. The SO [BΩH = 0.95 - 95% CrI (0.90, 0.99)], FA (BΩH = 0.92 - 95% CrI (0.87, 0.97), and FR (BΩH = 0.92 - 95% CrI (0.88, 0.97)] subscales displayed excellent reliability. The MSPSS displayed initial evidence of convergent and discriminant validity.ConclusionThe MSPSS demonstrated good psychometric properties and excellent reliability in a large Australian sample. This instrument can be applied in national surveys and provide evidence of the role of social support in the Australian population.

A Spiritual Revisal Visit to Holy Land - Israel

Recently, lots of people are talking about visiting the Holy Land — Israel especially those who believe in Jesus Christ. In this paper, I will qualitatively review the historical background of the Holy Land, introduce why people like to visit Israel (reasons) together with the religion cultural affairs of Jews. Indeed, there are five types of travelling: leisure travel; pilgrimage travel; experiential travel; diversionary mode; experimental model. I will discuss these visiting mode in details. In the research methodology, I will fully look into the revelation theology in the Bible, documentary analysis of churches that travelled Israel and the cluster sampling to question church followers who visit Holy Land. The quantitative part of the Holy Land travelling research will also be discussed in the data analysis. Indeed, I will develop the corresponding Bayesian Confirmatory Factor Analysis Model for the Hong Kong local Christians Israel visiting. Then we shall use the software — SpiceLogic to generate the policy for the travelling. The result shows that there is a mixed typology of Christians that is contradicted to the tourism model proposed by Erik Cohen. They visited Israel NOT purely because of religious reasons but also due to their depression (or worrying) about daily life affairs and their curiosity in Israel. Then I ended the data section with the convergence and reliability checking of each individual sub-variable of the collected data. It is concluded that, through the present study, the Christian tourism companies should be well cooperated with our churches to make advisement to my discovered type of Christian visitors together with some suitable spiritual revisal schemes followed after these targeted visitors’ travelling. Hence, this mixed type of Christians will get the spiritual exhilaration after the Israel Holy Land visiting. Lastly, it is hoped that the full Christian Israel travelling programme will become part of the future smart (from the email recruiting of participants to the final e-spiritual retrieving materials) and sustainable travelling.

On the Construct Validity of the Persian Version of Ohio State Teacher Efficacy Scale: The Case of Iran

Teacher efficacy may relate to their effectiveness in terms of class management, instructional strategies, and student achievement. Some questionnaires have been used to capture teachers' efficacy. The most frequently used one is theOhio State Teacher Efficacy Scale. The study examined the construct validity and reliability of the Persian version of the Ohio State Teacher Efficacy Scale (POSTES) with an available sample of 536 Iranian teachers of English. Their age ranged from 20 to 64 years. The data, ordinal in nature, were submitted to Bayesian confirmatory factor analysis, as computed in AMOS. Convergence Statistic (CS)was 1.0008, which was well below 1.002, the critical value, thereby demonstrating construct validity of the instrument. The reliability of the scale turned out to be high (α = .94). Given the fact that POSTES was both valid and reliable, it is safe to hold that this questionnaire is useful for obtaining information regarding Iranian English teachers' sense of self-efficacy.