Frailty models have emerged as a pivotal tool in survival analysis, offering a robust framework to account for unobserved heterogeneity and dependence between paired failure times. In bivariate ...

A procedure for estimating a bivariate density based on data that may be censored is described. After the data are transformed to the unit square, the bivariate density is estimated using linear ...

Bivariate survival models with discretely distributed frailty based on the major gene concept and applied to the data on related individuals such as twins and sibs can be used to estimate the ...

One of the objectives in the Northern Manhattan Stroke Study is to investigate the impact of stroke subtype on the functional status 2 years after the first ischemic stroke. A challenge in this ...

Leveraging AI to help analyze and visualize data gathered from a variety of data sets enables data-driven insights and fast analysis without the high costs of talent and technology. In today's ...

This course is available on the MRes/PhD in Management (Employment Relations and Human Resources) and MRes/PhD in Management (Organisational Behaviour). This course is available with permission as an ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...