Learn about multiple regression with interactions between categorical variables in survey data in Stata with data from the British crime survey (2007-2008) / Abigail-Kate Reid, Nick Allum.
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...
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Full Text (via SAGE) |
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| Main Authors: | , |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
London :
SAGE Publications, Ltd.,
2019.
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| Subjects: |
| 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 2007-2008 British Crime Survey. Specifically, we test whether confidence in the police is related to the relative deprivation of one's neighbourhood and whether or not respondents have been a victim of crime. 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 Stata. |
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| Physical Description: | 1 online resource : illustrations |
| ISBN: | 9781526479884 1526479885 |
| Source of Description, Etc. Note: | Description based on XML content. |