R is for revolution: A cutting-edge, free, open source statistical package

Steven Andrew Culpepper, Herman Aguinis

Research output: Contribution to journalReview articlepeer-review

Abstract

The authors review the open source statistical package R. R allows researchers to implement statistical techniques including linear modeling, linear and nonlinear multilevel modeling, factor and principal component analysis, structural equation modeling, item and reliability analysis, time series modeling, and meta-analysis, among others. R presents several advantages over other statistical packages because it is updated on an ongoing basis, is free, is capable of creating high-quality graphics that are difficult to create with other packages, and includes important simulation capabilities. Some limitations of R include the need to learn a new programming language, difficulties handling missing data for new users, and relatively limited support and documentation. R is not yet popular in the organizational sciences but, given its ongoing improvement and many positive features, we predict that it will soon be.

Original languageEnglish (US)
Pages (from-to)735-740
Number of pages6
JournalOrganizational Research Methods
Volume14
Issue number4
DOIs
StatePublished - Oct 2011
Externally publishedYes

Keywords

  • computer package
  • free software
  • Monte Carlo simulation
  • psychometrics
  • quantitative research
  • statistical computing

ASJC Scopus subject areas

  • Management of Technology and Innovation
  • Strategy and Management
  • Decision Sciences(all)

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