A Bayesian hierarchical regression model was developed to estimate the trends and projections by considering the hierarchy of the data set. For health service coverage, four scenarios were defined ...

Hierarchical modelling with partitioning of overall variance between trust level and patient level in a model that included patient age, gender and length of stay and responses to questions on whether ...

MATERIAL AND METHODS Study Area The approach to susceptibility to desertification at spatial and hierarchical scales aims to quantify the contribution of indices related to vegetation, climate and ...

Hierarchical Regression Model As the study’s objective is to determine whether CLED influences IOCs’ choice preferences for Chinese smartphones, we applied a hierarchical regression model. We assumed ...

Online regression is enabled through a sparse pseudo-point approximation of the GP posterior. To scale to large environments, we further consider spatial domain partitioning via a hierarchical tree ...

The main contributions are summarized as follows: • We propose a new interpretable hierarchical graph representation learning framework for brain network regression analysis. • Comparing to ...

Table 4. Summary of Hierarchical Regression Analysis for perceived implicit rationing of nursing care (PIRNCA) associated with outcome measures of Patient Safety Culture, Safety Culture Dimensions ...

We found that distributional regression with a sinh-arcsinh distribution replicated observed partner age distributions most accurately across three geographically diverse data sets. This framework can ...