Learn about multiple regression with interactions between continuous variables in survey data in R with data from the General Social Survey (2016) /
This SAGE Research Methods Dataset example introduces readers to interaction effects in multiple regression. Multiple regression techniques allow researchers to evaluate whether a continuous dependent variable is a linear function of two or more independent variables. This example demonstrates how t...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
London :
SAGE Publications, Ltd.,
2019.
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| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | This SAGE Research Methods Dataset example introduces readers to interaction effects in multiple regression. Multiple regression techniques allow researchers to evaluate whether a continuous dependent variable is a linear function of two or more independent variables. This example demonstrates how to compute and interpret product-term interactions between continuous variables in Ordinary Least Squares (OLS) regression using a subset of data from the 2016 General Social Survey. We test whether agreement with a statement that men should go out to work and women should look after the home and family is related to literacy and to belief in the role of government in providing support. In this example, readers are introduced to the basic theory and assumptions underlying this technique, the type of question this technique can be used to answer, and how to produce and report results. The dataset file is accompanied by a Teaching Guide, a Student Guide, and a How-to Guide for R. |
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| Physical Description: | 1 online resource : illustrations |
| ISBN: | 9781526496409 1526496402 |