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Article
Descriptive Statistics From Published Research: A Readily Available Alternative to Raw Data to Assess Analytic Reproducibility and Robustness:
Advances in Developing Human Resources (2019)
  • Kim Nimon, University of Texas at Tyler
  • David Conley, University of Texas at Tyler
  • Marvin Bontrager, Georgia Gwinnett College
  • Greggory L. Keiffer, Houston Baptist University
  • Bryn Hammack-Brown, Tarleton State University
Abstract
The Problem
Meta-science literature calls for data to be made openly available so that scholars and scholar-practitioners can validate published findings, a foundational step in the reproducibility spectrum. However, access to original research data is an ongoing dilemma in various disciplines, including human resource development.

The Solution
Scholars and scholar-practitioners have the opportunity to evaluate the credibility of previous studies without access to the original raw data. The use of descriptive statistics from published research offers an alternative to assess the reproducibility and robustness of selected prior research.

The Stakeholders
In addition to validating research before applying implications for practice in the field, practitioners could benefit from working with scholars and scholar-practitioners by assessing analytic robustness and reevaluating data through a new framework to address burgeoning organizational problems, potentially saving resources. Scholars can reimagine conceptual frameworks based on advances to theory and statistical analyses capabilities. For emerging scholars, the ability to validate prior research or apply new models using the information contained in a publication can create a learning opportunity to understand statistical analyses.
Keywords
  • descriptive statistics,
  • meta-science,
  • analytic reproducibility,
  • analytic robustness,
  • general linear model
Publication Date
November 1, 2019
DOI
10.1177/1523422319869853
Citation Information
Kim Nimon, David Conley, Marvin Bontrager, Greggory L. Keiffer, et al.. "Descriptive Statistics From Published Research: A Readily Available Alternative to Raw Data to Assess Analytic Reproducibility and Robustness:" Advances in Developing Human Resources Vol. 21 Iss. 4 (2019) p. 421 - 437
Available at: http://works.bepress.com/kim-nimon/10/