Linear mixed models (LMMs) are a powerful and established tool for studying genotype–phenotype relationships. A limitation of the LMM is that the model assumes Gaussian distributed residuals, a ...

Statistical modeling lies at the heart of data science. Well-crafted statistical models allow data scientists to draw conclusions about the world from the limited information present in their data. In ...

Methodological Comparison of Mapping the Expanded Prostate Cancer Index Composite to EuroQoL-5D-3L Using Cross-Sectional and Longitudinal Data: Secondary Analysis of NRG/RTOG 0415 The ability to ...

Let (Y, (X i ) 1≤i≤p ) be a real zero mean Gaussian vector and V be a subset of {1,...,p}. Suppose we are given n i.i.d. replications of this vector. We propose a new test for testing that Y is ...

Demand is at an all-time high for data analysts who can help organizations, technology companies, governments, and nonprofit agencies grasp their organizational, societal, and scientific needs. The ...

Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the response and ...

The primary purpose of this paper is to review a very few results on some basic elements of large sample theory in a restricted structural framework, as described in detail in the recent book by LeCam ...