Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 8 of 8 for “"Random effect models"”.
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Censored Regression Models With Applications to Infrastructure Degradation Studies
… the estimation and inference for regression models where the response variable is bounded or censored. In these conditions, least squares methods are not appropriate, although they are widely used. This dissertation develops a generalization of the Tobit censored regression model using …
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The effect of transition to renewable energy on stakeholders of energy companies: analyses of energy companies' financial and non-financial performance indices
… in the energy sector, there are concerns on the effect of such environmental performance management initiatives on the firms' Key Performance Indicators (KPI). Therefore, this study investigates whether the energy transition has a significant effect on energy companies' financial, environmental, …
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Dynamic Prediction of Disease Progression With Longitudinal Data
… and stability over conventional shared random effects models, validated through simulations and a real dataset comparison. Chapter 4 introduces the multi-layer backward joint model (MBJM) for dynamic prediction in clinical research, designed to efficiently handle multivariate …
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Class Size Reduction: Is It Worth The Cost?a Meta-analysis Of The Research
… report the most accurate information. Fixed and random effect models were used to ensure the distribution across different studies. A total of three studies were meta-analyzed for this research. The studies included in this research examined class size and student achievement for students in …
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The impact of environmental accountability on firm corporate lobbying behaviour: an empirical investigation of US listed firms
… lobbying spending. After running both the fixed effect and random effect models along with the Hausman test to determine which model was best applicable to the hypothesis, the random effect model illustrated optimal results concluding that firms that lobby more tend to be poor environmental …
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Time-to-Event Prediction Using Deep Learning Models: Application to GPU Failure Data
Neural network models gain significant popularity in recent years due to their ability to identify complex patterns. In the field of reliability research, efforts are made to develop neural network models for predictive reliability. However, research focused on utilizing neural networks to forecast …
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Disuguaglianze sociali nella salute, tra eterogeneità individuale e fattori sociali di rischio
… in health/BMI and to understand whether the effect of socio-economic factors on health/BMI varies over the life course or across cohorts. I first apply growth curves models, a special case of multilevel model for change, that enable us to model individual health trajectories in health and …
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Statistical Methods for Multi-type Recurrent Event Data Based on Monte Carlo EM Algorithms and Copula Frailties
… events model with multivariate Gaussian random effects (frailties) for the intensity functions. In this chapter, we present nonparametric baseline intensity functions and a multivariate Gaussian distribution for the multivariate correlated random effects. An MCEM algorithm with MCMC …