Academic literature on the topic 'Structural model equation'

This study tested a structural model, examining the relationship between a latent variable termed demoralization and measured variables (anxiety, depression and hopelessness) in a community sample of Canadian youth. The combined sample consisted of data collected from four independent studies from 2001 to 2005. Nine hundred and seventy one (n=971) participants in each of the previous four studies were high school students (grades 10-12) from three geographic locations: Calgary, Saskatchewan and Lethbridge. Participants completed a battery of self-report questionnaires including the Beck Anxiety Inventory (BAI), Beck Depression Inventory-Revised (BDI-II), Beck Hopelessness Scale (BHS), and demographic survey. Structural equation modeling was used for statistical analysis. The analysis revealed that the final model, including depression, anxiety and hopelessness and one latent variable demoralization, fit the data (chi-square value, X2 (2) =7.24, p<. 001, goodness of fit indices (CFI=0.99, NFI=0.98) and standardized error (0.05). Overall, the findings suggest that close relationships exist among depression, anxiety, hopelessness and demoralization. In addition, the model was stable across demographic variables: sex, grade, and location. Further, the model explains the relationship between sub-clinical anxiety, depression and hopelessness. These findings contribute to a theoretical framework, which has implications with educational and clinical interventions. The present findings will help guide further preventative research in examining demoralization as a precursor to sub-clinical anxiety and depression.<br>xi, 127 leaves ; 29 cm.

This study introduces a new model-free case influence measure (DOCR) to the SEM field and evaluates its performance compared to that of Mahalanobis Distance (MD) and Generalized Cook’s Distance (gCD) when the sample size, proportion of target cases to non-target cases, and type of model used to generate the data are manipulated. The findings suggest the DOCR measure generally performed better than MD and gCD in identifying the target cases across all simulated conditions. However, the performance of the DOCR measure under small sample size was not satisfactory, and it raised a red flag about the sensitivity of this measure to small sample sizes. Therefore, researchers and practitioners should only use the DOCR measure with sufficiently large sample sizes, but not larger than 600.

The normative development of language is often taken for granted, yet problems with language development can result in stress for the individual and family. A challenge with these language development problems lies within the contemporary education system, which assumes that children have appropriate skills when they begin school. The purpose of the study was to test a theoretical model of language readiness known as language-based cognitive fitness, which includes measures associated with structural concepts of language involving receptive language, expressive language, spontaneous narrative speech, and writing fluency. The sample included children from a private school who received an extensive battery of tests at admission and annually thereafter. Scores from a variety of cognitive measures were used in a structural equation modeling framework to test the model. Results demonstrated language-based cognitive fitness to be an interplay of verbal reasoning abilities, visual synthesis, and active analysis broadly representing receptive language, expressive language, spontaneous narrative expression, and writing fluency. Verbal reasoning, visual synthesis, and active analysis explained 91% of the variance in achievement. Implications for positive social change include an improved understanding for those who work with children's language development, specifically of the language structures responsible for language deficits and how these relate to overall cognitive fitness; interventions can be provided to help children more quickly make up language deficits.

Structural equation modelling (SEM) is carried out with the aim of testing hypotheses on the model of the researcher in a quantitative way, using the sampled data. Although SEM has developed in many aspects over the past few decades, there are still numerous advances which can make SEM an even more powerful technique. We propose representing the nal theoretical SEM by a Bayesian Network (BN), which we would like to call a Probabilistic Structural Equation Model (PSEM). With the PSEM, we can take things a step further and conduct inference by explicitly entering evidence into the network and performing di erent types of inferences. Because the direction of the inference is not an issue, various scenarios can be simulated using the BN. The augmentation of SEM with BN provides signi cant contributions to the eld. Firstly, structural learning can mine data for additional causal information which is not necessarily clear when hypothesising causality from theory. Secondly, the inference ability of the BN provides not only insight as mentioned before, but acts as an interactive tool as the `what-if' analysis is dynamic.<br>Mini Dissertation (MCom)--University of Pretoria, 2018.<br>Statistics<br>MCom<br>Unrestricted

The purpose of this study is twofold: (1) to examine the effects of knowledge on cognition and regulation of cognition on declarative knowledge, conditional knowledge, and procedural knowledge in geometry and (2) to examine the interrelationships among declarative knowledge, conditional knowledge, and procedural knowledge in geometry. The reciprocal relationships between metacognitive and knowledge factors were modeled by using data from tenth grade secondary school students. Structural equation modeling was used to test the hypothesized relationships of two metacognitive factors (knowledge of cognition, regulation of cognition) and three knowledge factors (declarative knowledge, conditional knowledge, procedural knowledge). The observed variables representing the latent variables were determined by carrying out exploratory factor analysis and confirmatory factor analysis for the metacognitive awareness inventory and geometry knowledge test separately. Major findings revealed: (1) Declarative knowledge significantly and positively influences conditional and procedural knowledge<br>(2) Procedural knowledge has a signitificant and positive direct effect on conditional knowledge<br>(3) Declarative knowledge has a positive indirect effect on conditional knowledge<br>(4) Knowledge of cognition significantly and positively influences procedural knowledge<br>(5) Regulation of cognition has a significant but negative direct effect on procedural knowledge<br>(6) Knowledge of cognition has positive indirect effects on conditional and procedural knowledge<br>(7) Regulation of cognition has negative indirect effects on conditional and procedural knowledge<br>(8) Knowledge of cognition and regulation of cognition have non-significant direct effect on declarative and conditional knowledge. The results showed that knowledge of cognition has the strongest direct effect on procedural knowledge and the direct effect of declarative knowledge on conditional knowledge is stronger than on procedural knowledge. In view of the findings considerable suggestions is provided for teachers, instructional designers, and mathematics education researchers.

Acceptance of information technology (IT) has remained a topic of interest for a last few decades. Several theories, specifically over the conceptualisation of the technology acceptance model (TAM) have emerged and they have been applied in different contexts to investigate new insights into the acceptance behaviour at individual and organisational levels. However, despite TAM’s maturity and validity in different contexts, very little published literature strives to extend its capability to predict individuals’ acceptance behaviour about an online banking information system (OBIS). A possible rational for this gap may be conceptualisation of the TAM under which individuals’ acceptance behaviour can only be predicted with two beliefs: perceived ease of use (PEOU) and perceived usefulness (PU). The evidence in literature shows that PU and PEOU beliefs are not sufficient; hence, they may not explain individuals’ acceptance behaviour in emerging contexts, such as online banking information systems, especially in developing economies such as Pakistan. There is therefore a need for inclusion of any additional factor that can enhance prediction of acceptance of online banking information system by potential users. Extending research on the TAM, this study developed and tested a model of OBIS acceptance. The proposed model integrated key constructs from the information systems acceptance research stream into the theoretical frame of the TAM and other theories from social psychology, such as the theory of reasoned action (TRA), theory of planned behaviour (TPB) and the TAM2. According to the proposed conceptual model, OBIS acceptance was determined by eight main factors, which included perceived usefulness, perceived ease of use, trust, technological self-efficacy, response time, output quality, accessibility, and terminology clarity. In this model, PU was hypothesised to be affected by PEOU, trust, technological self-efficacy (TSE), output quality (OQ) and response time (RT). In addition, PEOU was hypothesised to be determined by three external factors: TSE, accessibility and terminology clarity (TC). The model was tested on a sample of 353 Internet banking users in Pakistan. Using structural equation modelling with Analysis of Moment Structures (AMOS) software, data analysis showed considerable support for the extended hypothesised model. The result indicated that, in order of importance, PU, PEOU and trust explained 45.7 % of the variance in the acceptance behaviour. The trust and the TSE predicted 28.1 % of the variance in the PU. However, the hypothesised relationships between the PU and the PEOU, OQ and RT were found to be not significant. While in the PEOU, 21.8 % of the variance was predicted by the TSE, accessibility and TC. TSE was found to be a more influential determinant of the PEOU than the PU. The consideration of factors that have a significant influence on the acceptance of OBIS, as identified in this research, is important for the managers in the banking sector, especially in developing countries, in order to increase wider acceptance and use of these systems, which provide benefits to both the customers and the service providers.