Skip to main content

Multivariate Regression Analysis


This final chapter provides an introduction into multivariate regression modeling. We will cover the logic behind multiple regression modeling and explain the interpretation of a multivariate regression model. We will further cover the assumptions this type of model is based upon. Finally, and using our data, we will provide concrete examples on how to interpret a multiple regression model.


  • Multivariate Regression Model
  • Extra-curricular Activities
  • Standardized Beta Coefficients
  • Absolute Influence
  • Advanced Statistics Course

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This is a preview of subscription content, access via your institution.

Buying options

USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-319-99118-4_9
  • Chapter length: 12 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
USD   69.99
Price excludes VAT (USA)
  • ISBN: 978-3-319-99118-4
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Hardcover Book
USD   89.99
Price excludes VAT (USA)
Fig. 9.1
Fig. 9.2


  • Esarey, J., & Schwindt-Bayer, L. A. (2017). Women’s representation, accountability and corruption in democracies. British Journal of Political Science, 1–32.

    Google Scholar 

Further Reading

  • Since basically all books listed under bivariate correlation and regression analysis also cover multiple regression analysis, the books I present here go beyond the scope of this textbook here. These books could be interesting further reads, in particular to students, who want to learn more what is covered here.

    Google Scholar 

  • Heeringa, S. G., West, B. T., & Berglund, P. A. (2017). Applied survey data analysis. Boca Raton: Chapman and Hall/CRC. An overview of different approaches to analyze complex sample survey data. In addition to multiple linear regression analysis the topics covered include different types of maximum likelihood estimations such as logit, probit, and ordinal regression analysis, as well as survival or event history analysis.

    Google Scholar 

  • Lewis-Beck, C., & Lewis-Beck, M. (2015). Applied regression: An introduction (Vol. 22). Thousand Oaks: Sage A comprehensive introduction into different types of regression techniques.

    Google Scholar 

  • Pesaran, M. H. (2015). Time series and panel data econometrics. Oxford: Oxford University Press. Comprehensive introduction into different forms of time series models and panel data estimations.

    CrossRef  Google Scholar 

  • Wooldridge, J. M. (2015). Introductory econometrics: A modern approach. Mason, OH: Nelson Education. Comprehensive book about various regression techniques; it is, however, mathematically relatively advanced.

    Google Scholar 

Download references

Author information

Authors and Affiliations


Rights and permissions

Reprints and Permissions

Copyright information

© 2019 Springer International Publishing AG

About this chapter

Verify currency and authenticity via CrossMark

Cite this chapter

Stockemer, D. (2019). Multivariate Regression Analysis. In: Quantitative Methods for the Social Sciences. Springer, Cham.

Download citation

  • DOI:

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-99117-7

  • Online ISBN: 978-3-319-99118-4

  • eBook Packages: Social SciencesSocial Sciences (R0)