Spline Regression Models (Quantitative Applications in the Social Sciences)

Marsh, Lawrence C.; Cormier, David R.

ISBN 10: 0761924205 / ISBN 13: 9780761924203

Published by SAGE Publications, Inc, 2001

Seller Inventory # U9780761924203

Synopsis:

Spline Regression Models shows the nuts-and-bolts of using dummy variables to formulate and estimate various spline regression models. For some researchers this will involve situations where the number and location of the spline knots are known in advance, while others will need to determine the number and location of spline knots as part of the estimation process. Through the use of a number of straightforward examples, the authors will show readers how to work with both types of spline knot situations as well as offering practical, down-to-earth information on estimating splines.

About the Author: Lawrence C. Marsh is a professor emeritus in economics at the University of Notre Dame, where he taught statistics and graduate econometrics for 30 years, and served as visiting professor in psychology at Avila University in Kansas City, MO, where he taught statistics and research methods. He also taught applied regression analysis in the MBA program at the University of Chicago’s Booth School of Business in 2010. He served as director of Notre Dame’s PhD program in economics for 13 years and has served on over 80 PhD dissertation committees. He served as statistical design strategist and head of analytics for Internet company Adknowledge. He has published hundreds of articles in professional journals including Journal of Econometrics, Marketing Science, Statistics in Medicine, as well as book chapters and books, including the SAGE book: Spline Regression Models in 2002 (Chinese edition 2018), Brain on Fire in 2010, and Money Flow in a Dynamic Economy in 2020.

Bibliographic Details

Title: Spline Regression Models (Quantitative ...
Publisher: SAGE Publications, Inc
Publication Date: 2001
Binding: Soft cover
Condition: Very Good
Dust Jacket Condition: 48049069
Signed: 5/5/2026 6:25:08 PM
Edition: 1778005508.