MRCV: A package for analyzing categorical variables with multiple response options

Natalie A. Koziol, Christopher R. Bilder

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Multiple response categorical variables (MRCVs), also known as "pick any" or "choose all that apply" variables, summarize survey questions for which respondents are allowed to select more than one category response option. Traditional methods for analyzing the association between categorical variables are not appropriate with MRCVs due to the within-subject dependence among responses. We have developed the MRCV package as the first R package available to correctly analyze MRCV data. Statistical methods offered by our package include counterparts to traditional Pearson chi-square tests for independence and loglinear models, where bootstrap methods and Rao-Scott adjustments are relied on to obtain valid inferences. We demonstrate the primary functions within the package by analyzing data from a survey assessing the swine waste management practices of Kansas farmers.

Original languageEnglish (US)
Pages (from-to)144-150
Number of pages7
JournalR Journal
Volume6
Issue number1
StatePublished - 2014

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Multiple Responses
Categorical variable
Waste management
Statistical methods
Chi-squared test
Log-linear Models
Bootstrap Method
Statistical method
Adjustment
Choose
Categorical variables
Valid
Demonstrate

ASJC Scopus subject areas

  • Statistics and Probability
  • Numerical Analysis
  • Statistics, Probability and Uncertainty

Cite this

MRCV : A package for analyzing categorical variables with multiple response options. / Koziol, Natalie A.; Bilder, Christopher R.

In: R Journal, Vol. 6, No. 1, 2014, p. 144-150.

Research output: Contribution to journalArticle

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