The adjusted r-squared is helpful for multiple regression and corrects for erroneous regression, giving you a more accurate correlation coefficient. If you look at the multiple regression we did, ...

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, ...

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 ...

Scandinavian Journal of Statistics, Vol. 43, No. 4 (December 2016), pp. 1035-1045 (11 pages) Linear structural equation models, which relate random variables via linear inter-dependencies and Gaussian ...

This is a preview. Log in through your library . Abstract Motivated by examples from genetic association studies, this article considers the model selection problem in a general complex linear model ...