We introduce a very general "forward" method of data analysis that starts from a small, robustly chosen subset of the data and shows the effect of adding observations by a forward search. Powerful ...

In a transformation model h(Y) = X'β + ε for some smooth and usually monotone function h, we are often interested in the direction of β without knowing the exact form of h. We consider a projection of ...

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

In this module, we will introduce the basic conceptual framework for statistical modeling in general, and linear statistical models in particular. In this module, we will learn how to fit linear ...

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 ...