Please note: In order to keep Hive up to date and provide users with the best features, we are no longer able to fully support Internet Explorer. The site is still available to you, however some sections of the site may appear broken. We would encourage you to move to a more modern browser like Firefox, Edge or Chrome in order to experience the site fully.

General Linear Model : A Primer, PDF eBook

General Linear Model : A Primer PDF

PDF

Please note: eBooks can only be purchased with a UK issued credit card and all our eBooks (ePub and PDF) are DRM protected.

Description

General Linear Model methods are the most widely used in data analysis in applied empirical research.

Still, there exists no compact text that can be used in statistics courses and as a guide in data analysis.

This volume fills this void by introducing the General Linear Model (GLM), whose basic concept is that an observed variable can be explained from weighted independent variables plus an additive error term that reflects imperfections of the model and measurement error.

It also covers multivariate regression, analysis of variance, analysis under consideration of covariates, variable selection methods, symmetric regression, and the recently developed methods of recursive partitioning and direction dependence analysis.

Each method is formally derived and embedded in the GLM, and characteristics of these methods are highlighted.

Real-world data examples illustrate the application of each of these methods, and it is shown how results can be interpreted.

Information

Information