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Learn About Poisson regression in R with data from the Behavioral Risk Factor Surveillance System (2013) / 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:
  • 9781473961982 (online resource) :
Subject(s): DDC classification:
  • 001.422 23
Online resources: This dataset example introduces readers to Poisson regression. This technique allows researchers to evaluate whether a dependent variable that records a count of something is a function of one or more independent variables. The Poisson regression model is most commonly estimated via maximum likelihood estimation (MLE). This example uses a subset of data from the 2013 Behavioral Risk Factor Surveillance System (BRFSS) operated by the U.S. Centers for Disease Control. It presents an analysis of the number of servings of fruit per day respondents report eating as a function of gender, income, education, and whether or not they reported being physically active in the previous 30 days. An analysis like this allows researchers to evaluate factors that affect healthy eating habits, which may be helpful in designing health policy.
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This dataset example introduces readers to Poisson regression. This technique allows researchers to evaluate whether a dependent variable that records a count of something is a function of one or more independent variables. The Poisson regression model is most commonly estimated via maximum likelihood estimation (MLE). This example uses a subset of data from the 2013 Behavioral Risk Factor Surveillance System (BRFSS) operated by the U.S. Centers for Disease Control. It presents an analysis of the number of servings of fruit per day respondents report eating as a function of gender, income, education, and whether or not they reported being physically active in the previous 30 days. An analysis like this allows researchers to evaluate factors that affect healthy eating habits, which may be helpful in designing health policy.

Specialized.

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

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