Synonyms
Definition
Ordinary least-squares (OLS) models assume that the analysis is fitting a model of a relationship between one or more explanatory variables and a continuous or at least interval outcome variable that minimizes the sum of square errors, where an error is the difference between the actual and the predicted value of the outcome variable. The most common analytical method that utilizes OLS models is linear regression (with a single or multiple predictor variables).
Description
Ordinary least-squares (OLS) models assume that the analyst is fitting a model of a relationship between one or more explanatory variables and a continuous or at least interval outcome variable that minimizes the sum of square errors, where an error is the difference between the actual and the predicted value of the outcome variable. The most common analytical method that utilizes OLS models is linear regression (with a single or multiple...
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Cohen, J., Cohen, P., West, S., & Aiken, L. (2003). Applied multiple regression/correlation analysis for the behavioral sciences. Hillsdale, NJ: Lawrence Erlbaum Associates.
Hill, A. B. (1971). Principles of medical statistics (9th ed.). New York: Oxford University Press.
Hung, C., Liu, C., Yang, C., & Wang, S. (2012). Negative impact of migraine on quality of life after 4 weeks of treatment in patients with major depressive disorder. Psychiatry and Clinical Neurosciences, 66, 8–16.
Kleinbaum, D. G., Kupper, L. L., & Muller, K. E. (1988). Applied regression analysis and other multivariable methods. Belmont, CA: Duxbury Press.
Lavallee, L. F., Hatch, P. M., Michalos, A. C., & McKinley, T. (2007). Development of the contentment with life assessment scale (CLAS): Using daily life experiences to verify levels of self-reported life satisfaction. Social Indicators Research, 83(2), 201–244.
Michalos, A. C., & Kahlke, M. (2010). Arts and the perceived quality of life in British Columbia. Social Indicators Research, 96, 1–39.
Montgomery, D. C., Peck, E. A., & Vining, G. G. (2012). Introduction to linear regression analysis (4th ed.). New York: Wiley.
Tabachnick, B. G., & Fidell, L. S. (2001). Using multivariate statistics. Boston, MA: Allyn and Bacon.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer Science+Business Media Dordrecht
About this entry
Cite this entry
Zdaniuk, B. (2014). Ordinary Least-Squares (OLS) Model. In: Michalos, A.C. (eds) Encyclopedia of Quality of Life and Well-Being Research. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0753-5_2008
Download citation
DOI: https://doi.org/10.1007/978-94-007-0753-5_2008
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-0752-8
Online ISBN: 978-94-007-0753-5
eBook Packages: Humanities, Social Sciences and Law