Analyzing the Effect of Factors on Individuals’ Subjective Well-Being with Quantile Bayesian Structural Equation Modeling Approach by Zübeyde Çiçek, Nuran Bayram Arlı

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APPLICATION OF SEM AND QARDL MODELS IN THE PRACTICE OF ANALYSIS OF THE INFLUENCE OF EXCHANGE RATE VOLATILITY ON MACROECONOMIC INDICATORS by Roman Shchur, Andriy Pilko, Bohdan Chepyha, Mykhailo Bilyi, Sergii Stabias

“…The work uses the simultaneous simulative equations model (SEM) and the quantile autoregressive distributed lag model (QARDL), which made it possible to use their capabilities and form a linear and non-linear approach to assessing the impact of volatility on selected indicators in the short- and long-term. …”
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The Relevance of Cognitive and Affective Factors to Explain the Acceptance of Blockchain Use: The Case of Loyalty Programmes by Mar Souto-Romero, Mario Arias-Oliva, Jorge de Andrés-Sánchez, Miguel Llorens-Marín

“…A partial least squares-structural equation modelling analysis suggests that, to explain the expected response of BEHAV, only the positive relationships of the cognitive constructs with the response variable are significant. …”
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Enhanced Prediction of Soil Carbon via Encoder-Decoder Neural Networks for a Boreal Study Area in Northern Ontario by Rory Pittman, Baoxin Hu

“…These methods were able to effectively extract dominant features within predictor data and augment modeling accuracy. The obtained results were compared with those attained from structural equation modeling (SEM) and random forest (RF), as well as basic DNN and CNN models. …”
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Climate Change Risk, Performance, and Value Added in Agricultural Sector by Ramin Amani, Zanko Ghorbani, Zana Mozaffari

“…Methodology The general definition of quantile regression states that if the linear regression model is assumed as the following equation, we have: yi=ˊxiβτ+uτi.  0<τ<1                                                                                 (1) Quantτ(yi|xi)=xiβτ                                                                                  (2) Equation (2) shows the τth conditional quantile function of the y distribution under the condition of random variables x in which the following condition holds: Quantτ(uτi|xi)=0                                                                                              (3) In the quantile regression structure, the effect of observable features on the conditional distribution is estimated through the process of minimizing the absolute value of the error element. …”
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Unlocking academic achievement of nursing master’s students: ethical leadership, teacher-student relationship and growth mindset – a cross-sectional survey study by Duo Zhang, Haoyang Zheng, Ya Zhao, Xiaoxiao Wang, Qi Xiao, Ruiyi Zhao, Lan Wang, Kaili Hu, Zelin Chen, Yanrong Zhou

“…Data were analyzed using Pearson correlation analysis, structural equation model testing, and deviation correction quantile bootstrap method. …”
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Using satellite-derived attributes as proxies for soil carbon cycling to map carbon stocks in alpine grassland soils by Ren-Min Yang, Lai-Ming Huang, Zhifeng Yan, Xin Zhang, Shao-Jun Yan

“…We derived remote sensing indices such as gross primary production, soil respiration, soil moisture, land surface temperature, radiation, and soil disturbance and assessed the relationships between these indices and SOC stocks via partial least squares structural equation modeling (PLS-SEM). We evaluated the effectiveness of these indices in predicting SOC stocks, we compared PLS-SEM and quantile regression forest (QRF) models across different variable combinations, including static, intra-annual, and inter-annual information. …”
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