Generalizing the Regression Model

Techniques for Longitudinal and Contextual Analysis

Blair Wheaton author Marisa Young author

Format:Paperback

Publisher:SAGE Publications Inc

Published:2nd Mar '21

Currently unavailable, and unfortunately no date known when it will be back

Generalizing the Regression Model cover

This comprehensive text introduces regression, the general linear model, structural equation modeling, the hierarchical linear model, growth curve models, panel data, and event history models, and includes discussion of published implementations of each technique showing how it was used to address substantive and interesting research questions. It takes a step-by-step approach in the presentation of each topic, using mathematical derivations where necessary, but primarily emphasizing how the methods involved can be implemented, are used in addressing representative substantive problems than span a number of disciplines, and can be interpreted in words. The book demonstrates the analyses in STATA and SAS. Generalizing the Regression Model provides students with a bridge from the classroom to actual research practice and application.

Quantitative analyses are so often relegated to OLS techniques when they should not be. The authors more than adequately demonstrate the why, what, and how other procedures (GMM, SEM, panel regression, event history analysis to name a few) are far superior to the OLS approaches widely but inappropriately found in published research or used in practice. Kudos to them. -- Dane Joseph
Generalizing the Regression Model is a highly accessible textbook that covers a remarkable array of complex material with ease. Its applications and examples make the material intuitive and interesting for students to learn. -- Jennifer Hayes Clark

ISBN: 9781506342092

Dimensions: unknown

Weight: 1450g

688 pages