Most of the models are completed in a single file and implemented in a simple way. The machine learning part of the code does not use any external libraries, except for the loading part of the ONNX ...
What is a Gaussian Graphical Model ? A Gaussian graphical model captures conditional (in)dependencies among a set of variables. These are pairwise relations (partial correlations) controlling for the ...
Multilevel modelling has rapidly become established as the appropriate tool for modelling data with complex hierarchical structures. It is important for extending our understanding of social, ...
Trading off benefits and harms requires knowledge of the absolute risk reduction or risk difference, making risk difference a critical measure for decision making. The confidence interval of risk ...
Modeling species distributions over space and time is one of the major research topics in both ecology and conservation biology. Joint Species Distribution models (JSDMs) have recently been introduced ...
The analysis of factor structures is one of the most critical psychometric applications. Frequently, variables (i.e., items or indicators) resulting from questionnaires using ordinal items with 2–7 ...
We propose a strategy for building prior distributions that stabilize the estimation of complex “working models” when sample sizes are too small for standard statistical analysis. The stabilization is ...
Neighborhood characteristics have been associated with various facets of children’s health. This study explored whether adverse neighborhood conditions—particularly violence exposure and perceptions ...
Telehealth services have the potential to improve access to care, especially in rural or urban areas with scarce health care resources. Despite the potential benefits, telehealth has not been fully ...
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