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Learn about logistic regression 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:
  • 9781473961869 (online resource) :
Subject(s): DDC classification:
  • 001.422 23
Online resources: This dataset example introduces readers to logistic regression, often simply called logit. This technique allows researchers to evaluate whether a dichotomous dependent variable is a function of one or more independent variables. The logit 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 say Yes or No when asked whether they support granting legal status to all illegal immigrants who have held jobs and paid taxes in the U.S. for at least three years and have not been convicted of any felony crimes. An analysis like this allows researchers to evaluate public sentiment for possible changes in immigration policy.
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This dataset example introduces readers to logistic regression, often simply called logit. This technique allows researchers to evaluate whether a dichotomous dependent variable is a function of one or more independent variables. The logit 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 say Yes or No when asked whether they support granting legal status to all illegal immigrants who have held jobs and paid taxes in the U.S. for at least three years and have not been convicted of any felony crimes. An analysis like this allows researchers to evaluate public sentiment for possible changes in immigration policy.

Specialized.

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

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