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Goldilocks Rounding: Achieving Balance Between Accuracy and Parsimony in the Reporting of Relative Effect Estimates
Author(s) -
Jimmy T. Efird
Publication year - 2021
Publication title -
cancer informatics.
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.606
H-Index - 31
ISSN - 1176-9351
DOI - 10.1177/1176935120985132
Subject(s) - rounding , decimal , computer science , measure (data warehouse) , round off error , spurious relationship , statistics , confidence interval , interval (graph theory) , arithmetic , representation (politics) , numerosity adaptation effect , algorithm , data mining , mathematics , medicine , cognition , combinatorics , operating system , psychiatry , politics , political science , law
Researchers often report a measure to several decimal places more than what is sensible or realistic. Rounding involves replacing a number with a value of lesser accuracy while minimizing the practical loss of validity. This practice is generally acceptable to simplify data presentation and to facilitate the communication and comparison of research results. Rounding also may reduce spurious accuracy when the extraneous digits are not justified by the exactness of the recording instrument or data collection procedure. However, substituting a more explicit or simpler representation for an original measure may not be practicable or acceptable if an adequate degree of accuracy is not retained. The error introduced by rounding exact numbers may result in misleading conclusions and the interpretation of study findings. For example, rounding the upper confidence interval for a relative effect estimate of .996 to 2 decimal places may obscure the statistical significance of the result. When presenting the findings of a study, authors need to be careful that they do not report numbers that contain too few significant digits. Equally important, they should avoid providing more significant figures than are warranted to convey the underlying meaning of the result.

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