Learn about multiple regression with interactions between categorical variables in survey data in SPSS with data from the European 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 two categorical variables in Ordinary Least Squares (OLS) regression using a subset of data from the 2016 European Social Survey. Specifically, we test whether satisfaction with the economy is related to gender and whether respondents voted in the last national election. 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 SPSS. |
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| Physical Description: | 1 online resource : illustrations |
| ISBN: | 9781526480699 1526480697 |