Can I read Data Analysis: A Model Comparison Approach to Regression, ANOVA, and Beyond on EtoBox?

Data Analysis: A Model Comparison Approach to Regression, ANOVA, and Beyond by Joshua Correll & Abigail M. Folberg & Charles M. Judd & Gary H. McClelland & Carey S. Ryan is a nonfiction available to read on EtoBox.

What is Data Analysis: A Model Comparison Approach to Regression, ANOVA, and Beyond about?

This essential textbook provides an integrated treatment of data analysis for the social and behavioral sciences. It covers all the key statistical models in an integrated manner that relies on the comparison of models of data estimated under the rubric of the general linear model. The text describes the foundational logic of the unified model comparison framework. It then shows how this framework can be applied to increasingly complex models including multiple continuous and categorical predictors, as well as product predictors (i.e., interactions and nonlinear effects). The text also describes analyses of data that violate assumptions of independence, homogeneity, and normality. The analysis of nonindependent data is treated in some detail, covering standard repeated measures analysis of variance and providing an integrated introduction to multilevel or hierarchical linear models and logistic regression. Highlights of the fourth edition includeExpanded coverage of generalized linear models and logistic regression in particular A discussion of power and ethical statistical practice as it relates to the replication crisis An expanded collection of online resources such as PowerPoin

Who reads Data Analysis: A Model Comparison Approach to Regression, ANOVA, and Beyond?

Author

Joshua Correll & Abigail M. Folberg & Charles M. Judd & Gary H. McClelland & Carey S. Ryan

Publisher

Routledge

Published

2026

Language

EN

Category

nonfiction

Subjects

Computer Science, Organization And Data Processing, Stem