An important part of regression modeling is performing diagnostics to verify that assumptions behind the model are met and that there are no problems with the data that are skewing the results. This tutorial builds on prior posts covering simple and multiple regression as well as regression with nominal independent variables. The same data will be used here.
The variables used in this tutorial are:
vote_share (dependent variable): The percent of voters for a Republican candidate.

This tutorial shows how to fit a multiple regression model (that is, a linear regression with more than one independent variable) using Stata. The details of the underlying calculations can be found in our multiple regression tutorial. The data used in this post come from the More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior study from DiGrazia J, McKelvey K, Bollen J, Rojas F (2013), which investigated the relationship between social media mentions of candidates in the 2010 and 2012 US House elections with actual vote results.

This tutorial shows how to fit a multiple regression model (that is, a linear regression with more than one independent variable) using R. The details of the underlying calculations can be found in our multiple regression tutorial. The data used in this post come from the More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior study from DiGrazia J, McKelvey K, Bollen J, Rojas F (2013), which investigated the relationship between social media mentions of candidates in the 2010 and 2012 US House elections with actual vote results.

This tutorial shows how to fit a multiple regression model (that is, a linear regression with more than one independent variable) using SAS. The details of the underlying calculations can be found in our multiple regression tutorial. The data used in this post come from the More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior study from DiGrazia J, McKelvey K, Bollen J, Rojas F (2013), which investigated the relationship between social media mentions of candidates in the 2010 and 2012 US House elections with actual vote results.

This tutorial shows how to fit a multiple regression model (that is, a linear regression with more than one independent variable) using SPSS. The details of the underlying calculations can be found in our multiple regression tutorial. The data used in this post come from the More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior study from DiGrazia J, McKelvey K, Bollen J, Rojas F (2013), which investigated the relationship between social media mentions of candidates in the 2010 and 2012 US House elections with actual vote results.

This tutorial shows how to fit a simple regression model (that is, a linear regression with a single independent variable) using SAS. The details of the underlying calculations can be found in our simple regression tutorial. The data used in this post come from the More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior study from DiGrazia J, McKelvey K, Bollen J, Rojas F (2013), which investigated the relationship between social media mentions of candidates in the 2010 and 2012 US House elections with actual vote results.

This tutorial shows how to fit a simple regression model (that is, a linear regression with a single independent variable) using SPSS. The details of the underlying calculations can be found in our simple regression tutorial. The data used in this post come from the More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior study from DiGrazia J, McKelvey K, Bollen J, Rojas F (2013), which investigated the relationship between social media mentions of candidates in the 2010 and 2012 US House elections with actual vote results.

This tutorial shows how to fit a simple regression model (that is, a linear regression with a single independent variable) using R. The details of the underlying calculations can be found in our simple regression tutorial. The data used in this post come from the More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior study from DiGrazia J, McKelvey K, Bollen J, Rojas F (2013), which investigated the relationship between social media mentions of candidates in the 2010 and 2012 US House elections with actual vote results.

This tutorial shows how to fit a simple regression model (that is, a linear regression with a single independent variable) using Stata. The details of the underlying calculations can be found in our simple regression tutorial. The data used in this post come from the More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior study from DiGrazia J, McKelvey K, Bollen J, Rojas F (2013), which investigated the relationship between social media mentions of candidates in the 2010 and 2012 US House elections with actual vote results.

In our previous tutorials, we discussed simple regression and multiple regression with continuous variables, but what happens when our independent variable is nominal rather than interval?
The data used in this tutorial are again from the More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior study from DiGrazia J, McKelvey K, Bollen J, Rojas F (2013), which investigated the relationship between social media mentions of candidates in the 2010 and 2012 US House elections with actual vote results.