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Learn about ordered probit in R with data from the Cooperative Congressional Election Study (2012) / The Odum Institute.

Contributor(s): Material type: TextPublisher: London : SAGE Publications, 2016Description: 1 online resource : illustrations (colour)Content type:
  • text
  • still image
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781473961890 (online resource) :
Subject(s): DDC classification:
  • 001.422 23
Online resources: This dataset example introduces readers to ordered probit. This technique allows researchers to evaluate whether a categorical variable with three or more categories that follow some order is a function of one or more independent variables. The ordered probit model is most commonly estimated via maximum likelihood estimation (MLE). This example uses a subset of data from the 2012 Cooperative Congressional Election Study (CCES). It presents an analysis of whether survey respondents believe that laws covering the sale of firearms should be more strict, kept as they are, or less strict. This is measured on a 3-point scale. An analysis like this allows researchers to evaluate public sentiment for possible changes in gun control policies.
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Includes bibliographical references.

This dataset example introduces readers to ordered probit. This technique allows researchers to evaluate whether a categorical variable with three or more categories that follow some order is a function of one or more independent variables. The ordered probit model is most commonly estimated via maximum likelihood estimation (MLE). This example uses a subset of data from the 2012 Cooperative Congressional Election Study (CCES). It presents an analysis of whether survey respondents believe that laws covering the sale of firearms should be more strict, kept as they are, or less strict. This is measured on a 3-point scale. An analysis like this allows researchers to evaluate public sentiment for possible changes in gun control policies.

Specialized.

Description based on online resource; title from home page (viewed on January 8, 2016).

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