Skip to main content

Multiple Regression and the Race Implicit Attitudes Test (2012): Political Ideology and Racial Attitudes

By: Nick Allum Published: 2015 | Product: SAGE Research Methods Datasets
Data Type: Survey Experiment
University of Essex logo
+- LessMore information
Search form
Not Found

This dataset example introduces readers to multiple regression. This technique allows researchers to evaluate whether a continuous dependent variable is a linear function of two or more independent variables. The multiple linear regression model is most commonly estimated via ordinary least squares (OLS), and is sometimes called OLS regression. This example describes multiple regression, discusses the assumptions underlying it, and shows how to estimate and interpret multiple regression models. We illustrate multiple regression using a subset of data from the Race Implicit Attitudes Test 2012 (IAT2012). Specifically, we examine the relationship between political ideology and a measure of implicit racism with self-reported attitudes to African Americans. This is an important topic for understanding the psychological and political bases of racial prejudice in America.

Direct Prerequisites: Simple ...

Looks like you do not have access to this content.

To view more content or download guides and data files, please log in or subscribe below.

Looks like you do not have access to this content.

About This Dataset
Data Source Citation

Xu, K., Nosek, B. A., & Greenwald, A. G. (2014). Race IAT 2002-2013. Open Science Framework [Dataset]. Retrieved from:

Full title of originating dataset

Race IAT 2002–2013

Data author(s) and affiliations

Kaiyuan Xu, University of Washington, US

Brian Nosek, University of Virginia Center for Open Science, US

Anthony Greenwald, University of Washington, US

First publication date

18 March 2014

Sample/sampling procedures

Online opt-in

Data collection dates

23 December 2002 to 31 December 2012

Time frame of analysis


Unit of analysis


Location covered by data


Links to SRM content
  • Wolf, C., & Best, H. (2014). Linear regression. In H. Best, & C. Wolf (Eds.), The SAGE handbook of regression analysis and causal inference (pp. 57–83). London: SAGE Publications Ltd. doi:
  • Kahane, L. H. (2008). Multiple regression analysis. In Regression basics. (2nd ed., pp. 59–79). Thousand Oaks, CA: SAGE Publications, Inc. doi:
  • Stolzenberg, R. (2004). Multiple regression analysis. In M. Hardy, & A. Bryman (Eds.), Handbook of data analysis (pp. 165–208). London, England: SAGE Publications, Ltd. doi:
List of variables


Overall IAT D score


Thermology - African Americans


Thermology - European Americans


Political ID with a 7-point scale

Methods Map
Multiple regression