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Causal-formative indicators are often used in social science research. To achieve identification in causal-formative indicator modeling, constraints need to be applied. A conventional method is to constrain the weight of a formative indicator to be 1. The selection of which indicator to have the fixed weight, however, may influence statistical inferences of the structural path coefficients from the causal-formative construct to outcomes. Another conventional method is to use equal weights (e.g., 1) and assumes that all indicators equally contribute to the latent construct, which can be a strong assumption. To address the limitations of the conventional methods, we proposed an alternative constraint method, in which the sum of the weights is constrained to be a constant. We analytically studied the relations and interpretations of structural path coefficients from the constraint methods, and the results showed that the proposed method yields better interpretations of path coefficients. Simulation studies were conducted to compare the performance of the weight constraint methods in causal-formative indicator modeling with one or two outcomes. Results showed that higher biases in the path coefficient estimates were observed from the conventional methods compared to the proposed method. The proposed method had ignorable bias and satisfactory coverage rates in the studied conditions. This study emphasizes the importance of using an appropriate weight constraint method in causal-formative indicator modeling. [ABSTRACT FROM AUTHOR]

Abstract Background The main challenge in heritage education is to identify the verbs—and their hierarchical relations—that explain heritage learning as based on empirical evidence. The Heritage Learning Sequence (HLS) selects seven verbs (Knowing-Understanding-Respecting-Valuing-Caring-Enjoying-Transmitting) on the basis of (a) theoretical studies, (b) analyses of international standards, and (c) evaluation of heritage education programs. The study has the following objectives: (a) to clarify the heritage learning process; (b) to test a theoretical model that groups the verbs that make up the Heritage Learning Sequence (HLS), as well as the relationships between them; (c) to identify possible sub-models that explain the different heritage learning itineraries. Methods The Q-Herilearn scale (previously calibrated using SEM and IRT models) was administered to $$N = 1454$$ N = 1454 individuals, focusing on seven factors (corresponding to each HLS verb) that measure heritage learning. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used as a general analytical strategy. Findings The results obtained provided sufficient guarantees to validate the HLS and showed the adequate explanatory and predictive power and general fit of the proposed model (Heritage Learning Model); all twelve hypothesized direct influence relations between the main verbs that define heritage learning were confirmed. The statistical significance values suggested the existence of other internal subsequences that could be explored in further studies. Contribution Learning modeling provides a key structural framework for (a) the design of effective, efficient, and comprehensive tools to measure heritage learning and (b) their operationalization in heritage education designs.

Translation abstract The cable net models for the Olympic roof landscape in Munich. Last witnesses of model analysisAs part of the research project “Last Witnesses measurement models in civil engineering – scientific significance and preservation”, funded by the DFG in the priority programme 2255 ”Construction as Cultural Heritage“, the few surviving measurement models from the era of model analysis were examined and documented. This report provides insight into the physical models built for the Munich Olympic roof and their use in the planning process. The limitations of the model analysis method for large cable net constructions become clear and how this promoted digitalization in architecture and structural engineering. [ABSTRACT FROM AUTHOR]

Background: The main challenge in heritage education is to identify the verbs—and their hierarchical relations—that explain heritage learning as based on empirical evidence. The Heritage Learning Sequence (HLS) selects seven verbs (Knowing-Understanding-Respecting-Valuing-Caring-Enjoying-Transmitting) on the basis of (a) theoretical studies, (b) analyses of international standards, and (c) evaluation of heritage education programs. The study has the following objectives: (a) to clarify the heritage learning process; (b) to test a theoretical model that groups the verbs that make up the Heritage Learning Sequence (HLS), as well as the relationships between them; (c) to identify possible sub-models that explain the different heritage learning itineraries. Methods: The Q-Herilearn scale (previously calibrated using SEM and IRT models) was administered to N = 1454 individuals, focusing on seven factors (corresponding to each HLS verb) that measure heritage learning. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used as a general analytical strategy. Findings: The results obtained provided sufficient guarantees to validate the HLS and showed the adequate explanatory and predictive power and general fit of the proposed model (Heritage Learning Model); all twelve hypothesized direct influence relations between the main verbs that define heritage learning were confirmed. The statistical significance values suggested the existence of other internal subsequences that could be explored in further studies. Contribution: Learning modeling provides a key structural framework for (a) the design of effective, efficient, and comprehensive tools to measure heritage learning and (b) their operationalization in heritage education designs. [ABSTRACT FROM AUTHOR]

Many methods have been developed since the 1980s to measure Brand Equity (BE). These methods range from theoretical and pragmatic approaches to qualitative methods that determine the rankings of remembrance, emotionality, and valuation based on the likelihood of purchasing a good, or service. The goal of this systematic review was to identify gaps in the literature and provide recommendations for future research by analyzing and summarizing the available data on models used to quantify BE. A systematic search of Dialnet, Ebsco, Google Scholar, Isi We of Knowledge, Redalyc, Science Direct, Scopus, Scielo, and Web of Science was performed using PRISMA principles. Of the 551 abstracts screened, only 23 met inclusion criteria. The review showed that no model allows for a comprehensive evaluation of BE. This makes it easier for us to understand and recognize their benefits, and drawbacks. Although there are many variations, none has been adequately verified to be reliably quantified. The combination of variables between the models indicates that the measurement does not produce an agreement between the theoretical and pragmatic. Everybody tries to appreciate the intangible, yet they all overlook branding messaging. Our findings shows that a thorough proposal incorporating a model that enables the inclusion of both tangible and intangible BE factors is required.

Just as receptive emotional abilities, productive emotional abilities are essential for social communication. Although individual differences in receptive emotional abilities, such as perceiving and recognizing emotions, are well-investigated, individual differences in productive emotional abilities, such as the ability to express emotions in the face, are largely neglected. Consequently, little is known about how emotion expression abilities fit in a nomological network of related abilities and typical behavior. We developed a multitask battery for measuring the ability to pose emotional expressions scored with facial expression recognition software. With three multivariate studies (n1 = 237; n2 = 141; n3 = 123), we test competing measurement models of emotion posing and relate this construct with other socio-emotional traits and cognitive abilities. We replicate the measurement model that includes a general factor of emotion posing, a nested task-specific factor, and emotion-specific factors. The emotion-posing ability factor is moderately to strongly related to receptive socio-emotional abilities, weakly related to general cognitive abilities, and weakly related to extraversion. This is strong evidence that emotion posing is a cognitive interpersonal ability. This new understanding of abilities in emotion communication opens a gateway for studying individual differences in social interaction. [ABSTRACT FROM AUTHOR]

Surveys often add reverse-coded questions to monitor respondents with insufficient effort responses (IERs) but often wrongly assume that all respondents consistently answer all questions with full effort. By contrast, this study expanded the mixture model for IERs and ran a simulation via LatentGOLD to show the harmful consequences of ignoring IERs to positively and negatively worded questions: less test reliability, bias and less accuracy in slope and intercept parameters. We showed its practical application to two public data sets: Machiavellianism (five-point scale) and self-reported depression (four-point scale). [ABSTRACT FROM AUTHOR]

Rapid advances in psychology and technology open opportunities and present challenges beyond familiar forms of educational assessment and measurement. Viewing assessment through the perspectives of complex adaptive sociocognitive systems and argumentation helps us extend the concepts and methods of educational measurement to new forms of assessment, such as those involving interaction in simulation environments and automated evaluation of performances. I summarize key ideas for doing so and point to the roles of measurement models and their relation to sociocognitive systems and assessment arguments. A game-based learning assessment SimCityEDU: Pollution Challenge! is used to illustrate ideas. [ABSTRACT FROM AUTHOR]

In order to explore the effective path to improve the efficiency of industrial water pollution governance efficiency (WGE), this study takes 27 prefecture-level cities in the Yangtze River Delta urban agglomeration in China as the research object, measures WGE through the improved SBM model, and tests the impact of WGE drivers using the spatial Durbin model (SDM). The study found that environmental pollution governance investment (EPGI) is positively correlated with WGE, and industrial agglomeration status (IAS) has inhibitory effects on the improvement of WGE. By testing IAS2, it was determined that the impact of IAS on WGE has a "U"-shaped relationship. The direct impact of EPGI on WGE is 0.5016, and the indirect impact on WGE is 0.6428; the direct impact of IAS on WGE is −0.3036, and the indirect impact on WGE is −0.5158. Among the other tested impact drivers, per capita GDP (PCG), industrial structure (IS), and level of technological innovation (TIL) are positively correlated with the dependent variable WGE, while energy consumption intensity (ECI), environmental regulation intensity (ERI), and degree of openness to foreign investment (FIR) are negatively correlated with the dependent variable WGE. In addition to the impact of the aforementioned main drivers, IAS and EPGI, these six drivers also largely influence and determine the final impact on WGE. [ABSTRACT FROM AUTHOR]

We review the development of path model fit measures for latent variable models and highlight how they are different from global fit measures. Next, we consider findings from two published simulation articles that reach different conclusions about the effectiveness of one path model fit measure (RMSEA-P). We then report the results of a new simulation study aimed at resolving the questions of whether and how the RMSEA-P should be used by organizational researchers. These results show that the RMSEA-P and its confidence interval is very effective with multiple indicator models at identifying misspecifications across large and small sample sizes and is effective at identifying true models at moderate to large sample sizes. We conclude with recommendations for how the RMSEA-P can be incorporated along with other information into model evaluation. [ABSTRACT FROM AUTHOR]

Survival analysis has several advantages, including the ability to handle incomplete data. In general, the explanatory variables used in survival analysis are manifest variables. In other fields such as social sciences, variables such as perception, attitudes, and psychology are often involved in statistical analysis. This research aims to model cox proportional hazard regression on data with latent variable types. Research was conducted in the banking sector using Likert scale questionnaire data. It will examine how the assessment of the 5C variable in the form of a latent variable relates to the time of delay in credit payments. Confirmatory Factor Analysis (CFA) was used to form a re ectively latent variable indicator model which was then formed into a cox proportional hazards regression model. The results show that all 5C variable assessments in uence the speed of credit payments. The novelty in this research lies in the use of indicator analysis models to form latent variables before undergoing survival. The resulting interpretation and conclusions are expected to provide more in-depth information because they include the relationship between survival time and indicators. [ABSTRACT FROM AUTHOR]

This research study investigates the importance consumers place on four restaurant dining facets (design, ambience, sociability, food and beverage) to ascertain how these elements contribute to memorable dining experience (MDEs). Restaurant formality and restaurant dining involvement were explored as additional influencing factors within the context of MDEs. Data were collected using an online survey administered to a sample of American diners. Through a measurement model approach, all four facets were found to define restaurant dining environment under MDEs. The findings provide meaningful insights to restaurant managers about how the dining environment of a restaurant can influence consumers' experience in terms of co-creating memorability. These insights are particularly relevant in the post-pandemic era, when the way consumers interact with restaurant environments may change. [ABSTRACT FROM AUTHOR]

The demands to improve electronic government systems are increasing due to the large gap in the unsuccessful implementation in government. This study aimed to develop a measurement model consisting of policy, governance, and service, resources (usage) variables with their indicators to reduce the gap. A quantitative method was used with structural equation modelling (SEM) analysis based on partial least square (PLS) variance using SmartPLS version 3.0 software. Data collection for this study involved the direct distribution of questionnaires to 320 respondents, resulting in a successful collection rate of 95.3%. Subsequently, the collected data underwent analysis using the stages of SEM techniques. The results of the study show that the developed measurement models and indicators can be used as measuring tools for the execution of e-government. The developed model exhibits a satisfactory level of predictive relevance concerning the relationships among the variables, namely policy, governance, service, and usage. Furthermore, hypothesis testing was conducted to assess the validity of the proposed hypotheses within the model. [ABSTRACT FROM AUTHOR]

Confirmatory factor analyses (CFA) are widely used in the organizational literature. As a result, understanding how to properly conduct these analyses, report the results, and interpret their implications is critically important for advancing organizational research. The goal of this paper is to summarize the complexities of CFA models and, therefore, to provide a resource for journal reviewers and researchers who are using CFA in their research. The topics covered in this paper include the estimation process, power analyses, model fit, and model modifications, among other things. In addition, this paper concludes with a checklist that summarizes the key points that are discussed and can be used to evaluate future studies that incorporate CFA. [ABSTRACT FROM AUTHOR]

To address the challenge of solving aircraft's visual navigation results using scene matching, this paper introduces the spherical EPnP positioning posture-solving method, which incorporates the threshold value for the central angle and the construction of a measurement model. The detailed steps are as follows: Firstly, the positioning coordinate model of the Earth's surface is constructed to ensure the expression of the three-dimensional coordinates of the Earth's surface. The positioning is then solved by employing the EPnP positioning posture-solving algorithm on the constructed data model. Secondly, by comparing and analyzing the positioning posture values of approximate plane coordinates, the critical value is determined, which serves as a reference for plane calculations. Lastly, a theoretical measurement model for visual height and central angle is constructed, taking into account the decided central angle threshold value. The simulation experiment demonstrates that using spherical coordinates as input results in an average positioning precision that is 16.42 percent higher compared to using plane coordinates as input. When the central angle is less than 0.5 degrees and the surface area is smaller than 55850 2 square meters, the positioning precision of plane coordinates is comparable to that of spherical coordinates. In such instances, the sphere can be approximated as flat. The findings of this study provide important theoretical guidance for further research on scene-matching positioning posture solving. These results hold significant implications for both theoretical research and engineering applications. [ABSTRACT FROM AUTHOR]

This article analyzes the studies on energy poverty and its measurement between 2004 and 2022. A search of the Web of Science database with the keyword "energy poverty measurement" yielded 195 articles, among which 69 articles were found. In the study, first of all, information about the definition of energy poverty, the problems it causes and its determining criteria. In the next step, other determinants of energy poverty are explained with the help of graphs and tables. In the methodology section, the articles are analyzed in detail according to the economic development of the countries and the measurement models used. Finally, conclusions and recommendations are presented, and future work is suggested to find a universally accepted measurement model. [ABSTRACT FROM AUTHOR]

People often appear to conflate anger and disgust, seemingly using expressions of both emotions interchangeably in response to moral violations. Yet, anger and moral disgust differ in their antecedents and consequences. These empirical observations are associated with two broad theoretical perspectives: one describes expressions of moral disgust as metaphors for anger, whereas the other describes moral disgust as functionally distinct from anger. Both accounts have received empirical support from separate and seemingly inconsistent literatures. The present study seeks to resolve this inconsistency by focusing on the different ways moral emotions have been measured. We formalise three theoretical models of moral emotions: one in which expressions of disgust are purely associated with anger (but not physiological disgust), one in which disgust and anger are fully separated and have distinct functions, and an integrative model that accommodates both metaphorical use in language and distinctive function. We test these models on responses to moral violations (four studies; N = 1608). Our results suggest that moral disgust has distinct functions, but that expressions of moral disgust are sometimes used to convey moralistic anger. These findings have implications for the theoretical status and measurement of moral emotions. [ABSTRACT FROM AUTHOR]

Edge service computing is an emerging paradigm for computing, storage, and communication services to optimize edge framework latency and cost based on mobile edge computing (MEC) devices. The devices are battery-enabled and have limited communication and computation resources. X consolidation is a major issue in distributed heterogeneous MEC orchestrations, where X represents the task scheduling/device selection/channel selection/offloading strategy. The network entities need to enhance network performance under uncertain circumstances for such orchestrations. Haphazard X consolidation leads to abnormal resource and energy usage, quality of service (QoS) and latency of the edge framework. However, this study concentrates on analysing the impact of reinforcement learning-based edge resource consolidation models. The models are classified according to functionality, including device resource management, service request allocation, device selection, and offloading types. Finally, the article discusses and highlights some unresolved challenges for further study on MEC orchestration to enhance offloading strategy and resource management, as well as device and channel selection efficiency. [ABSTRACT FROM AUTHOR]

Just as receptive emotional abilities, productive emotional abilities are essential for social communication. Although individual differences in receptive emotional abilities, such as perceiving and recognizing emotions, are well-investigated, individual differences in productive emotional abilities, such as the ability to express emotions in the face, are largely neglected. Consequently, little is known about how emotion expression abilities fit in a nomological network of related abilities and typical behavior. We developed a multitask battery for measuring the ability to pose emotional expressions scored with facial expression recognition software. With three multivariate studies (n1 = 237; n2 = 141; n3 = 123), we test competing measurement models of emotion posing and relate this construct with other socio-emotional traits and cognitive abilities. We replicate the measurement model that includes a general factor of emotion posing, a nested task-specific factor, and emotion-specific factors. The emotion-posing ability factor is moderately to strongly related to receptive socio-emotional abilities, weakly related to general cognitive abilities, and weakly related to extraversion. This is strong evidence that emotion posing is a cognitive interpersonal ability. This new understanding of abilities in emotion communication opens a gateway for studying individual differences in social interaction.

The relevant evolution of social networks and the expansion of digitalization has led to significant changes in the classical processes used by Moroccan companies in different fields such as marketing, human resources management, etc. This paper investigates the effects of digitalization on the attractiveness of Moroccan companies in terms of recruitment and safeguarding these constructs by using structural equation models according to the PLS approach. The study was carried out to touch 74 companies in different sectors. The study showed positive relationships between management support, digitalization, and recruitment performance (defined as the attractiveness of a company for recruitment and federalization of employees). The results show that the T-statistics are equal to 67.55, 6.862, and 5.941, respectively. The Q² value is 0.884 for scanning and 0.937 for performance, which means that the model is predictive in nature. The GoF is 1.388, which means that model is sufficiently large for the overall validity of the PLS model. While jobseeker behavior and competitive intensity did not affect recruitment performance because the test T-statistics is less than 1.64, the two factors have no moderating effect as the p-values are 0.228 and 0.082, respectively, exceeding the threshold of 0.05.

Abstract Background Tracking clinical outcomes during therapy can be useful for improving both clinical practice and research. For repeated data collection, short, reliable, and valid measures of central aspects of psychopathology are necessary. The current paper investigates the psychometric properties of two short surveys for measuring central dimensions of psychopathology in youth. Methods We investigated the factor structure and validity of the Norwegian translations of the Behavior and Feelings Survey (BFS) and the Brief Problem Monitor (BPM). The BFS has previously shown a two-factor structure and indications of validity as a measure of internalizing and externalizing problems in youth. The BPM has support for a three-factor structure of internalizing, externalizing, and attention problems. In our sample of 503 patients (56% female, age 6 to 18) in a Norwegian outpatient clinic, we conducted confirmatory factor analyses to test the assumed measurement models and further considered the concurrent validity of the measures. Results Internal reliability of both measures were good. The results suggest that the assumed measurement models for both questionnaires only partly fit our data but that subscales of the BFS and BPM still indicate convergent validity. Scores on subscales (internalizing and externalizing problems) on both measures converged with relevant subscales as well as with relevant groups of diagnoses. Conclusions Alternative measurement models, and the usefulness and limitations of these short-form questionnaires for internalizing and externalizing problems, are discussed.

Fog computing brings computational services near the network edge to meet the latency constraints of cyber-physical System (CPS) applications. Edge devices enable limited computational capacity and energy availability that hamper end user performance. We designed a novel performance measurement index to gauge a device’s resource capacity. This examination addresses the offloading mechanism issues, where the end user (EU) offloads a part of its workload to a nearby edge server (ES). Sometimes, the ES further offloads the workload to another ES or cloud server to achieve reliable performance because of limited resources (such as storage and computation). The manuscript aims to reduce the service offloading rate by selecting a potential device or server to accomplish a low average latency and service completion time to meet the deadline constraints of sub-divided services. In this regard, an adaptive online status predictive model design is significant for prognosticating the asset requirement of arrived services to make float decisions. Consequently, the development of a reinforcement learning-based flexible x-scheduling (RFXS) approach resolves the service offloading issues, where x = service/resource for producing the low latency and high performance of the network. Our approach to the theoretical bound and computational complexity is derived by formulating the system efficiency. A quadratic restraint mechanism is employed to formulate the service optimization issue according to a set of measurements, as well as the behavioural association rate and adulation factor. Our system managed an average 0.89% of the service offloading rate, with 39 ms of delay over complex scenarios (using three servers with a 50% service arrival rate). The simulation outcomes confirm that the proposed scheme attained a low offloading uncertainty, and is suitable for simulating heterogeneous CPS frameworks. [ABSTRACT FROM AUTHOR]

The success and satisfaction of students with online courses is significantly impacted by the sequencing of learning objectives and activities. Equally critical is designing online degree programs and structuring multiple courses to reduce learners' cognitive load and attain maximum learning success. In its current form, the evaluation of program design is complex and done primarily using stakeholders' perceptions and qualitative methods, which are subjective. Emerging technologies produce enormous amounts of educational data that have the potential to lead to evidence-based practice to reform the design of study programs. Although a few studies adopt such data-driven approaches to evaluate and enhance study programs, remarkably little is known about the sequencing of learning objectives and the influence of their mastery in one course on performance across subsequent courses. This study aims to assess the interdependency of learning objectives from multiple courses in a MOOC-based program by drawing on an interdisciplinary approach intersecting analytic techniques and measurement models. Situated in the context of professional leadership skill development, we ground our findings in leadership theory and how learners acquire skills over time and across varying contexts. [ABSTRACT FROM AUTHOR]

In this paper, we highlight the importance of distilling the computational assessments of constructed responses to validate the indicators/proxies of constructs/trins using an empirical illustration in automated summary evaluation. We present the validation of the Inbuilt Rubric (IR) method that maps rubrics into vector spaces for concepts' assessment. Specifically, we improved and validated its scores' performance using latent variables, a common approach in psychometrics. We also validated a new hierarchical vector space, namely a bifactor IR. 205 Spanish undergraduate students produced 615 summaries of three different texts that were evaluated by human raters and different versions of the IR method using latent semantic analysis (LSA). The computational scores were validated using multiple linear regressions and different latent variable models like CFAs or SEMs. Convergent and discriminant validity was found for the IR scores using human rater scores as validity criteria. While this study was conducted in the Spanish language, the proposed scheme is language-independent and applicable to any language. We highlight four main conclusions: (1) Accurate performance can be observed in topic-detection tasks without hundreds/thousands of pre-scored samples required in supervised models. (2) Convergent/discriminant validity can be improved using measurement models for computational scores as they adjust for measurement errors. (3) Nouns embedded in fragments of instructional text can be an affordable alternative to use the IR method. (4) Hierarchical models, like the bifactor IR, can increase the validity of computational assessments evaluating general and specific knowledge in vector space models. R code is provided to apply the classic and bifactor IR method. [ABSTRACT FROM AUTHOR]

Land fragmentation is one of the most important factors hindering the mechanization and scale of agriculture. To further alleviate the negative impact of arable land fragmentation, a more accurate model for measuring arable land fragmentation is needed. Using 0.1 resolution UAV images and farm survey data, we obtained spatial and tenure data of farming land in Baidu Village through ArcGis and other software, and analyzed the results and correlations of farming plot area, plot shape and plot dispersion indicators in the study area. A road accessibility index that integrates terrain slope and road network is proposed to characterize the dispersion of land parcels for the first time, and is compared with two road accessibility models that do not take into account terrain slope and road network. The results show that the dispersion index of farm plots is the most influential indicator on the fragmentation of farm plots, followed by the area index of farm plots, and finally the shape index of farm plots; the new model of measuring the fragmentation of farm plots based on natural surface elements and road networks is closer to the real situation and more accurate in portraying the degree of fragmentation of farm plots.

To address the challenge of solving aircraft’s visual navigation results using scene matching, this paper introduces the spherical EPnP positioning posture-solving method, which incorporates the threshold value for the central angle and the construction of a measurement model. The detailed steps are as follows: Firstly, the positioning coordinate model of the Earth’s surface is constructed to ensure the expression of the three-dimensional coordinates of the Earth’s surface. The positioning is then solved by employing the EPnP positioning posture-solving algorithm on the constructed data model. Secondly, by comparing and analyzing the positioning posture values of approximate plane coordinates, the critical value is determined, which serves as a reference for plane calculations. Lastly, a theoretical measurement model for visual height and central angle is constructed, taking into account the decided central angle threshold value. The simulation experiment demonstrates that using spherical coordinates as input results in an average positioning precision that is 16.42 percent higher compared to using plane coordinates as input. When the central angle is less than 0.5 degrees and the surface area is smaller than 558502 square meters, the positioning precision of plane coordinates is comparable to that of spherical coordinates. In such instances, the sphere can be approximated as flat. The findings of this study provide important theoretical guidance for further research on scene-matching positioning posture solving. These results hold significant implications for both theoretical research and engineering applications.

Background: Tracking clinical outcomes during therapy can be useful for improving both clinical practice and research. For repeated data collection, short, reliable, and valid measures of central aspects of psychopathology are necessary. The current paper investigates the psychometric properties of two short surveys for measuring central dimensions of psychopathology in youth. Methods: We investigated the factor structure and validity of the Norwegian translations of the Behavior and Feelings Survey (BFS) and the Brief Problem Monitor (BPM). The BFS has previously shown a two-factor structure and indications of validity as a measure of internalizing and externalizing problems in youth. The BPM has support for a three-factor structure of internalizing, externalizing, and attention problems. In our sample of 503 patients (56% female, age 6 to 18) in a Norwegian outpatient clinic, we conducted confirmatory factor analyses to test the assumed measurement models and further considered the concurrent validity of the measures. Results: Internal reliability of both measures were good. The results suggest that the assumed measurement models for both questionnaires only partly fit our data but that subscales of the BFS and BPM still indicate convergent validity. Scores on subscales (internalizing and externalizing problems) on both measures converged with relevant subscales as well as with relevant groups of diagnoses. Conclusions: Alternative measurement models, and the usefulness and limitations of these short-form questionnaires for internalizing and externalizing problems, are discussed. [ABSTRACT FROM AUTHOR]

Researchers around the world are applying the recently revised Portrait Value Questionnaire (PVQ-RR) to measure the 19 values in Schwartz's refined values theory. We assessed the internal reliability, circular structure, measurement model, and measurement invariance of values measured by this questionnaire across 49 cultural groups (N = 53,472) and 32 language versions. The PVQ-RR reliably measured 15 of the 19 values in the vast majority of groups and two others in most groups. The fit of the theory-based measurement models supported the differentiation of almost all values in every cultural group. Almost all values were measured invariantly across groups at the configural and metric level. A multidimensional scaling analysis revealed that the PVQ-RR perfectly reproduced the theorized order of the 19 values around the circle across groups. The current study established the PVQ-RR as a sound instrument to measure and to compare the hierarchies and correlates of values across cultures. [ABSTRACT FROM AUTHOR]

Accounting is a logical knowledge tool based on a system of rules that thinking must follow in order to achieve goals. This objective generally takes into account the construction of the true image of reality, using the accounting principles that influence the quality of accounting information. This study highlights the assessing methods for the quality of accounting information. The analysis shows that there are certain methods that are used to measure and assess the quality and usefulness of accounting information to determine the extent to which the financial statements match each of the qualitative characteristics. [ABSTRACT FROM AUTHOR]

Finke, Scheiner, Giurfa, and Avarguès-Weber (2023) published correlational data on the performance of honeybees (Apis mellifera) in three learning tasks (associative, reversal, and negative patterning, capturing the domains of operant conditioning , executive-functioning-like ability , and inhibition plus configural processing , respectively) evaluated under both visual and olfactory stimulus conditions. They speculate that general cognitive ability (GCA) may be weakly causing all-positive correlations between performance in these different learning modalities, but do not formally test this possibility. A factor-analytic model applied to Finke et al. (2023) data revealed the presence of two perfectly congruent GCA factors (one for each stimulus condition). Both exhibited all-positive loadings, with the visual factor accounting for 46.8% of the performance variance and the olfactory factor accounting for 52.3%. Diagnostic statistics confirmed that in both stimulus conditions, the correlation matrices were adequate for factor analysis. These findings support extant hypotheses that GCA influences covariation between cognitive measures in honeybees, and constitute the first formal potential demonstration of GCA in an invertebrate. It is argued that GCA might be ubiquitous with respect to metazoans possessing organized nervous systems, perhaps because it convergently evolved multiple times in independent phylogenies, this being a key prediction of Christopher Chabris' Law of General Intelligence. Indeed, GCA has now been identified in insect, avian, mammal, and fish taxa. Some "primordial" aspects of GCA may even by basal to metazoans, and experiments employing Caenorhabditis elegans are suggested that could potentially shed light on such aspects. The findings are also strikingly inconsistent with evolutionary and comparative psychological theories positing a "modules first" understanding of cognitive evolution, such as one recent proposal that smaller brains cannot accommodate structures that give rise to GCA. Other theoretical implications of these findings are discussed. • The present study performed exploratory factor analyses on correlational matrices based on cognitive data on honey bees. • Horn's parallel models recommended the extraction of a general cognitive ability factor. • The measurement models accounted from 46.8% to 52.3% of the variance. • Principal Axis Factor analyses supported the presence of a general cognitive ability factor. • This factor loaded positively onto all cognitive indictors. [ABSTRACT FROM AUTHOR]

Fair value's advantages, disadvantages and ideology have been debated thoroughly by academics and practitioners for decades. The few implementation papers which do exist are primarily concerned with developed economies. This gap is despite the prior literature acknowledging the likely difficulties of fair value use by less developed markets and economies. This paper contributes to addressing this gap by providing an analysis of the extent and use of fair value by Johannesburg Stock Exchange (JSE) Top 40 companies for the period 2013–2017. This paper finds limited use of fair value by JSE Top 40 companies. On average, only 184 assets and liabilities make use of fair value each year and this has not changed significantly over time. Most fair value use is by the financial services industry (41%) and for financial instruments (80%). Critically, only 28% of all financial elements made use of Level 1 inputs, and only 15% were classified overall as Level 1 inputs. The findings suggest Level 1 inputs are not widely available for financial elements and are rarely available for non-financial assets. When fair values are used for non-financial assets, this is mainly for investment property, commodity-inventories and impairment tests. Because of the reliance on Level 2 and 3 inputs, the results suggest fair value is a costly measurement basis to implement in South Africa and frequently requires management judgement. The consequence is that many fair values are susceptible to bias and manipulation. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this study was to review existing healthcare service quality-measurement models. Design/methodology/approach – A review of the literature was conducted utilizing keywords “healthcare”, “service quality”, “measurement models”, “SERVQUAL”, “SERVPERF”, “HEALTHQUAL”, “PubHosQual” and “HospitalQual”. These investigations were selected from the “Emerald”, “ABI/Inform”, “ScienceDirect” and “EBSCOhost” databases. A range of studies used in the makeup of the healthcare quality-measurement model for a 36 years period (1979 to 2015) were examined in an exhaustive survey of the literature. Of 137 studies reviewed, 74 studies were selected for analysis. Findings – As yet, no consensus has been reached among scholars on the definition and indicators and factors of the quality of the healthcare services. Moreover, most of the current models are of Western origin and incongruent with the cultural and economic contexts of developing countries. The previous studies create scales resembling the generic measures of service quality, which may not be completely appropriate for assessing the perceived quality of healthcare services. Furthermore, previous studies were too narrow, overemphasizing the quality of healthcare only as far as the functional aspect of the services were concerned and paying too little attention to the technical aspects, using the experience of healthcare providers. These results have much room for failures. This is therefore advising healthcare organizations that need to develop their own models for measuring the quality of their services. Originality/value – Generic models no longer suffice in measuring the quality of healthcare services. Developing countries should try and develop their own models for measuring the quality of healthcare services.

The paper presents a detailed theoretical background for coordinate measurement uncertainty evaluation by means of Type B evaluation method, taking into account information on accuracy of a coordinate measuring system given with the formula for maximum permissible errors of length measurement and verification test results. A proposal for evaluation of the verification test results is made. A measurement model based on the point-plane distance equation is presented. A detailed analysis of the partial derivatives (sensitivity factors in an uncertainty budget) of the measurement model is presented. The analyses of measurement uncertainty for different geometrical characteristicswere conducted using this measurement model. Examples of uncertainty evaluation for geometrical deviations are presented: position of a point related to a datum plane and flatness in the case of convex or concave surfaces. The examples include detailed uncertainty budgets.

Theories in the domain of healthcare service quality have evolved over time. To consolidate the healthcare service dimensions, there are various studies illustrating measurement models for the healthcare industry. The objective of this paper is to review various SERVQUAL models and practices in the domain of the healthcare industry. The nature of the paper is conceptual with a review of various SERVQUAL models referred fromsecondary databases. The findings from the review conclude that Western contexts and models are different from the healthcare context of developing countries especially in Africa as a result of the cultural background and socio-economic variations. The healthcare service quality measurement model needs to be explored further in terms of its operationalization indeveloping an acceptable model reflecting on crosscultural settings and country wise. [ABSTRACT FROM AUTHOR]

Abstract Background Research concerning the causes and consequences of intimate partner violence (IPV), particularly in less developed areas of the world, has become prominent in the last two decades. Although a number of potential causal factors have been investigated the current consensus is that attitudes toward IPV on the individual level, likely representing perceptions of normative behavior, and the normative acceptability of IPV on the aggregate level likely play key roles. Measurement of both is generally approached through either binary indicators of acceptability of any type of IPV or additive composite indexes of multiple indicators. Both strategies imply untested assumptions which potentially have important implications for both research into the causes and consequences of IPV as well as interventions aimed to reduce its prevalence. Methods Using survey data from rural Senegal collected in 2014, this analysis estimates latent class measurement models of attitudes concerning the acceptability of IPV. We investigate the dimensional structure of IPV ideation and test the parallel indicator assumption implicit in common measurement strategies, as well as structural and measurement invariance between men and women. Results We find that a two-class model of the acceptability of IPV in which the conditional probability of class membership is allowed to vary between the sexes is preferred for both men and women. Though the assumption of structural invariance between men and women is supported, measurement invariance and the assumption of parallel indicators (or equivalence of indicators used) are not. Conclusions Measurement strategies conventionally used to operationalize the acceptability of IPV, key to modeling perceptions of norms around IPV, are a poor fit to the data used here. Research concerning the measurement characteristics of IPV acceptability is a precondition for adequate investigation of its causes and consequences, as well as for intervention efforts aimed at reducing or eliminating IPV.

In this paper, a bibliometric and documentary analysis of leadership, leadership styles and leadership methods of identification in companies over the last decade was carried out. To this end, a systematic review of scientific publications contained in Scopus databases between 2009 and 2019 was performed. The search engines of the National Library System of the National University of Colombia and Google Scholar were used to retrieve the publications. A total of 950 scientific papers were reviewed for the bibliometric analysis. As a result of this analysis, different leadership styles were identified, the number of which varied depending both on the author and on the identification method. The study concludes that the transformational leadership style prevails in the scientific literature. In addition, the analysis found that the Multifactorial Leadership Questionnaire (MLQ) is the instrument that allows identifying in greater depth the leadership style characteristics.

This article explores the use of migration data for the measurement of life satisfaction as an alternative to data collection by standardized interviews. It starts with the development of a field theoretic model of the impact of life satisfaction on international migration, which is subsequently reversed such that it explains life satisfaction by means of migration data. Empirical tests with data about the migration from Poland to other European countries confirm the main hypotheses of the model. However, the accuracy of ex-post predictions about the quality of life of a target country depends on the number of earlier (Polish) immigrants, who are a source of information for others considering to emigrate. Thus, under certain conditions the model may be used for imputing the life satisfaction of countries for which the respective information is missing. The model is even useful if the information for model calibration is completely missing: the article shows how in this situation migration data may be used for ranking countries with regard to their not directly measurable life satisfaction. [ABSTRACT FROM AUTHOR]

Health is a multidimensional concept that is challenging to measure, and in the rapidly evolving developmental changes that occur during the first 21 years of human life, requires a dynamic approach to accurately capture the transitions, and overall arc of a complex process of internal and external interactions. We propose an approach that integrates a lifecourse framework with a layered series of assessments, each layer using a many to many mapping, to converge on four fundamental dimensions of health measurement-Potential, Adaptability, Performance, and Experience. The four dimensions can conceptually be mapped onto a plane with each edge of the resulting quadrilateral corresponding to one dimension and each dimensions assessment calibrated against a theoretical ideal. As the plane evolves over time, the sequential measurements will form a volume. We term such a model the Prism Model, and describe conceptually how single domain assessments can be built up to generate the holistic description through the vehicle of a layer of Exemplar Cases. The model is theoretical but future work can use the framework and principles to generate scalable and adaptable applications that can unify and improve the precision of serial measurements that integrate environmental and physiologic influences to improve the science of child health measurement.