Why All Researchers Should Report Effect Sizes and Their Confidence Intervals: Paving the Way for Meta–Analysis and Evidence–Based Management Practices
Restricted accessEditorialFirst published online July, 2015
Why All Researchers Should Report Effect Sizes and Their Confidence Intervals: Paving the Way for Meta–Analysis and Evidence–Based Management Practices
The growing body of empirical entrepreneurship studies and the advent of meta–analytic methodologies create new opportunities to develop evidence–based management practices. To support research on evidence–based practices, empirical studies should report meta–analysis relevant information, such as standardized effect–size measures and their confidence intervals. The corresponding changes in reporting practices are simple and straight forward—yet they promise strong contributions to the systematic accumulation of entrepreneurship knowledge over time.
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References
1.
American Psychological Association. (2010). Publication manual of the American Psychological Association. Washington, DC: Author.
CohenJ. (1994). The earth is round (p < 0.05). American Psychologist, 49(12), 997–1003.
4.
CummingG. (2011). Understanding the new statistics: Effect sizes, confidence intervals, and meta–analysis. New York: Routledge.
5.
EllisP.D. (2010). The essential guide to effect sizes: Statistical power, meta–analysis and the interpretation of research results. New York: Cambridge University Press.
6.
GigerenzerG. (2004). Mindless statistics. Journal of Socio–Economics, 33, 587–606.
7.
GlaserG.V. (1976). Primary, secondary and meta–analysis of research. Education Researcher, 10, 3–8.
8.
HuntM. (1997). How science takes stock: The story of meta–analysis. New York: Russell Sage Foundation.
9.
MoherD. & OlkinI. (1995). Meta–analysis of randomized controlled trials: A concern for standards. JAMA: The Journal of the American Medical Association, 274(24), 1962–1964.
10.
OrlitzkyM. (2012). How can significance tests be deinstitutionalized?Organizational Research Methods, 15(2), 199–228.
11.
PfefferJ. & SuttonR.I. (2006). Hard facts, dangerous half–truths and total nonsense: Profiting from evidence–based management. Cambridge, MA: Harvard Business School Press.
