Multiple Regression: A Primer

by Paul D. Allison

Overview

Multiple regression is at the heart of social science data analysis, because it deals with explanations and correlations. This book is a complete introduction to this statistical method.

This textbook is designed for the first social statistics course a student takes and, unlike other titles aimed at a higher level, has been specifically written with the undergraduate student in mind.

Product Details

ISBN-13:	9780761985334
Publisher:	SAGE Publications
Publication date:	12/29/1998
Series:	Undergraduate Research Methods & Statistics in the Social Sciences
Edition description:	New Edition
Pages:	224
Product dimensions:	6.00(w) x 9.00(h) x (d)

About the Author

Paul D. Allison, Ph.D., is Professor of Sociology at the University of Pennsylvania where he teaches graduate courses in methods and statistics. He is also the founder and president of Statistical Horizons LLC which offers short courses on a wide variety of statistical topics.

After completing his doctorate in sociology at the University of Wisconsin, he did postdoctoral study in statistics at the University of Chicago and the University of Pennsylvania. He has published eight books and more than 60 articles on topics that include linear regression, log-linear analysis, logistic regression, structural equation models, inequality measures, missing data, and survival analysis.

Much of his early research focused on career patterns of academic scientists. At present, his principal research is on methods for analyzing longitudinal data, especially those for determining the causes and consequences of events, and on methods for handling missing data.

A former Guggenheim Fellow, Allison received the 2001 Lazarsfeld Award for distinguished contributions to sociological methodology. In 2010 he was named a Fellow of the American Statistical Association. He is also a two-time winner of the American Statistical Association’s award for “Excellence in Continuing Education.”

Table of Contents

What Is Multiple Regression?
How Do I Interpret Multiple Regression Results?
What Can Go Wrong with Multiple Regression?
How Do I Run a Multiple Regression?
How Does Bivariate Regression Work?
What Are the Assumptions of Multiple Regression?
What Can Be Done about Multicollinearity?
How Can Multiple Regression Handle Nonlinear Relationships?
How Is Multiple Regression Related to Other Statistical Techniques?

Editorial Reviews

"I find the concept for this approach to teaching undergraduate research methods and statistics innovative and exciting. The idea of ‘core’ texts supplemented by satellite volumes covering specific, important topics makes absolute sense."

Barbara Heyl