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Communication in Natural Resource Management: Agreement between and Disagreement within Stakeholder Groups
Published 2013-06-01Subjects: Get full text
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Analysis of factors influencing the accumulation of psychological capital of college students under the theory of cognitive psychology
Published 2024-01-01“…In this paper, from the perspective of cognitive psychology, we intend to introduce the origin, classification, application conditions, and estimation methods of the network autocorrelation model, compare the differences between the conventional linear model and network autocorrelation model in processing relationship data through a simulation study, explore the factors influencing the accumulation of psychological capital of college students, and analyze the internal and external factors influencing the psychological capital of college students through the results of questionnaire survey. …”
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Associations within school-based same-sex friendship networks of children’s physical activity and sedentary behaviours: a cross-sectional social network analysis
Published 2018-02-01“…Network autocorrelation between girls was weaker, with 0.13 (95% CI: 0.06 to 0.19) for MVPA and 0.11 (95% CI: 0.05 to 0.17) for sedentary time. …”
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Sensitivity of MRQAP tests to collinearity and autocorrelation conditions
Published 2007“…We assess the statistical bias (type I error rate) and statistical power of the set of five methods, including DSP, across a variety of conditions of network autocorrelation, of spuriousness (size of confounder effect), and of skewness in the data. …”
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Assessing built environment walkability using activity-space summary measures
Published 2015-06-01“…Based on objective walkability measures of the street blocks, we use three summary measures for walkability within activity spaces: i) the average walkability score across block segments, ii) the standard deviation, and iii) the network autocorrelation. We assess the method using data from an empirical study of built environment walkability and walking behavior in Salt Lake City, Utah. …”
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Socio-demographic determinants of motorcycle speeding in Maha Sarakham, Thailand.
Published 2020-01-01“…We ran linear network autocorrelation models (lnam) to account for the data's social network structure. …”
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The Loneliness of Low-Income Older Adults in a Federal Volunteering Program: A Network Perspective
Published 2023-12-01“…This study collected information on the social networks within an SCP in a Midwest Metropolitan and feelings of loneliness among low-income Russian, Khmer, Somali, Nepali, and English-speaking older volunteers ( N = 41). A linear network autocorrelation model (LNAM) was constructed to quantify how volunteers’ loneliness is correlated with their peers’ loneliness within SCP. …”
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A Spatial-Filtering Zero-Inflated Approach to the Estimation of the Gravity Model of Trade
Published 2018-02-01“…Nevertheless, as trade flows are not independent from each other due to spatial and network autocorrelation, these methods may lead to biased parameter estimates. …”
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Dengue importation into Europe: A network connectivity-based approach.
Published 2020-01-01“…We also incorporated network autocorrelation within a GLMM framework to investigate the propensity of a European country to receive an imported case, by virtue of its position within the air transport network. …”
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Employees’ healthy eating and physical activity: the role of colleague encouragement and behaviour
Published 2022-11-01“…Methods: We used the European Sustainable Workforce Survey, with data on 4345 employees in 402 teams in 113 organisations. We used network autocorrelation models, which resemble regression models, to study to what extent employee encouragement is related to fruit and vegetable consumption, and physical activity. …”
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Social network correlates of free and purchased insecticide-treated bed nets in rural Uganda
Published 2022-11-01“…Linear regression models that account for network autocorrelation were fitted to estimate the association between households’ bed net ownership ratios and bed net ownership ratios of network peer households, adjusting for sociodemographics and network centrality. …”
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