Generally speaking, there are two types of outcomes (i.e. response) in statistical analysis: continuous and categorical responses. Linear Models (LM) are one of the most commonly used statistical ...

Many response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, modeling the state damaged/not damaged of cells after treated with ...

This paper develops a class of models to deal with missing data from longitudinal studies. We assume that separate models for the primary response and missingness (e.g., number of missed visits) are ...

Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 57, No. 1 (2008), pp. 75-87 (13 pages) Complex survey sampling is often used to sample a fraction of a large finite ...

Interpretability has drawn increasing attention in machine learning. Partially linear additive models provide an attractive middle ground between the simplicity of generalized linear model and the ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...