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36 results for “Structural Equation Modelling”
Dataset for the publication: Factors associated with risky drinking decisions in a virtual reality alcohol prevention simulation: A structural equation model
<p>This dataset includes the data from the publication <em>Factors associated with risky drinking decisions in a virtual reality alcohol prevention simulation: A structural equation model. </em>The first table sheet lists the data of the variables; the second table sheet describes the coding of the variables. </p>
Components related to ethical decision making in medical science students: A structural equation model
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Linking socioeconomic inequalities and type 2 diabetes through obesity and lifestyle factors among Mexican adults: a structural equations modeling approach
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Data from: Identifying drivers of breeding success in a long-distance migrant using structural equation modelling
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Data from: Estimating latent individual demographic heterogeneity using structural equation models
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Data from: Phylogenetic structural equation modelling reveals no need for an 'origin' of the leaf economics spectrum
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Supplementary material 1 from: Grace JB (2022) General guidance for custom-built structural equation models. One Ecosystem 7: e72780. https://doi.org/10.3897/oneeco.7.e72780
General guidance for custom-built structural equation models
Application of health belief model for the assessment of COVID-19 preventive behavior and its determinants among students: A structural equation modeling analysis
<p><strong>Background:</strong> COVID-19 is a new pandemic that poses a threat to people globally. In Ethiopia, where classrooms are limited, students are at higher risk for COVID-19 unless they take consistent preventative actions. However, there is a lack of evidence in the study area regarding student compliance with COVID-19 preventive behavior (CPB) and its predictors.</p> <p><strong>Objective:</strong> This study aimed to assess CPB and its predictors among students based on the perspective of the Health Belief Model (HBM).</p> <p><strong>Method and materials:</strong> A school-based cross-sectional survey was conducted from November to December 2020 to evaluate the determinants of CPB among high school students using a self-administered structured questionnaire. 370 participants were selected using stratified simple random sampling. Descriptive statistics were used to summarize data, and partial least squares structural equation modeling (PLS-SEM) analyses to evaluate the measurement and structural models proposed by the HBM and to identify associations between HBM variables. A T-value of > 1.96 with 95% CI and a P-value of < 0.05 were used to declare the statistical significance of path coefficients.</p> <p><strong> Result:</strong> A total of 370 students participated with a response rate of 92%. The median (interquartile range) age of the participants (51.9% females) was 18 (2) years. Only 97 (26.2%), 121 (32.7%), and 108 (29.2%) of the students had good practice in keeping physical distance, frequent hand washing, and facemask use respectively. The HBM explained 43% of the variance in CPB. Perceived barrier (β= - 0.15, p < 0.001) and self-efficacy (β= 0.51, p <0.001) were significant predictors of student compliance to CPB. Moreover, the measurement model demonstrated that the instrument had acceptable reliability and validity.</p> <p><strong>Conclusion and recommendations:</strong> COVID-19 prevention practice is quite low among students. HBM demonstrated adequate predictive utility in predicting CPBs among students, where perceived barriers and self-efficacy emerged as significant predictors of CPBs. According to the findings of this study, theory-based behavioral change interventions are urgently required for students to improve their prevention practice. Furthermore, these interventions will be effective if they are designed to remove barriers to CPBs and improve students' self-efficacy in taking preventive measures.</p>
Structural equation models to interpret genome-wide association studies for morphological and productive traits in soybean [Glycine max (L.)]
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Structural equation modeling (Data Analysis)
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Application of health belief model for the assessment of COVID-19 preventive behavior and its determinants among students: A structural equation modeling analysis
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Structural equation model mediation analysis dataset
<p>The dataset was obtained from responses by study participants who were asked to answer four short sections of a survey questionnaire. The first three sections related to three factors (constructs) thought to influence precision medicine implementation. The fourth section was designed to elicit demographic information about participants, including their age, gender and organizational affiliations. Regarding factors influencing precision medicine implementation, participants were asked to rate their considered opinion for the factors on a five point “strongly agree” to “strongly disagree” Likert-type scale. The data was then used for further mediation and other analyses.</p>
The Effects of Spiritual Needs on Spiritual Well-Being in Patients With Brain Tumors: A Structural Equation Modeling Approach
ClinicalTrials.gov study NCT05356507. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Dieting, obsessive-compulsive thoughts, and orthorexia nervosa: assessing the mediating role of worries about food through a structural equation model approach
<p><strong>Background: </strong>Orthorexia Nervosa (ON) is a condition characterized by an obsessive focus on healthy eating, inflexible dietary rules, and persistent preoccupations with food. Despite it has been recently the subject of increasingly relevant studies, little is known about the mechanisms that might foster ON symptoms.</p> <p><strong>Objective: </strong>This study used a structural equation modeling approach to test the mediating effect of thoughts, worries, and preoccupations about food on the relationship that eating disorders (EDs) attitudes (e.g., dieting) and obsessive-compulsive thoughts and symptoms have with ON in a large community sample. It was hypothesized that the effect of dieting and obsessive-compulsive thoughts and symptoms on would be partially mediated by the presence of thoughts, worries, and preoccupations about food.</p> <p><strong>Methods: </strong>Data from a cross-sectional sample of 1328 participants (females = 976) recruited from the general population were asked to fill in an online survey comprising the Eating Attitude Test-26 (EAT-26), the Obsessive-compulsive subscale of the Symptom Checklist-90Revised (SCL-90R-OC) and the Orthorexia Scale-15 (ORTO-15).</p> <p><strong>Results: </strong>Structural equation models indicated that both obsessive-compulsive thoughts and symptoms and dieting had a direct effect on and that food preoccupation partially mediated these relationships.</p> <p><strong>Conclusion: </strong>These findings provide novel insight into the nature of ON that could aid its conceptualization and treatment.</p>
Dataset for "Understanding the Predictors of Perceived Disability in Older Adults: A Bayesian Structural Equation Model Approach" study
<p>SF-12, CES-D, GES, Activity level & GARS responses sourced from 473 participants via online questinnaire. </p>
Data from: The mediating effect of perceived Coach's emotional support to Life satisfaction, Curiosity and Sports engagement: a Partial Least Square-Structural Equation Model
<p>This data set is from the study titled, "The mediating effect of perceived Coach’s emotional support to Life satisfaction, Curiosity and Sports engagement: a Partial Least Square-Structural Equation Model."</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.