Indexes and boundaries for "quantitative significance" in statistical decisions.

Details

Serval ID
serval:BIB_32384791300F
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Indexes and boundaries for "quantitative significance" in statistical decisions.
Journal
Journal of Clinical Epidemiology
Author(s)
Burnand Bernard, Kernan Walter N., Feinstein Alvan R
ISSN
0895-4356 (Print)
ISSN-L
0895-4356
Publication state
Published
Issued date
1990
Peer-reviewed
Oui
Volume
43
Number
12
Pages
1273-1284
Language
english
Abstract
Boundaries for delta, representing a "quantitatively significant" or "substantively impressive" distinction, have not been established, analogous to the boundary of alpha, usually set at 0.05, for the stochastic or probabilistic component of "statistical significance". To determine what boundaries are being used for the "quantitative" decisions, we reviewed pertinent articles in three general medical journals. For each contrast of two means, contrast of two rates, or correlation coefficient, we noted the investigators' decisions about stochastic significance, stated in P values or confidence intervals, and about quantitative significance, indicated by interpretive comments. The boundaries between impressive and unimpressive distinctions were best formed by a ratio of greater than or equal to 1.2 for the smaller to the larger mean in 546 comparisons, by a standardized increment of greater than or equal to 0.28 and odds ratio of greater than or equal to 2.2 in 392 comparisons of two rates; and by an r value of greater than or equal to 0.32 in 154 correlation coefficients. Additional boundaries were also identified for "substantially" and "highly" significant quantitative distinctions. Although the proposed boundaries should be kept flexible, indexes and boundaries for decisions about "quantitative significance" are particularly useful when a value of delta must be chosen for calculating sample size before the research is done, and when the "statistical significance" of completed research is appraised for its quantitative as well as stochastic components.
Keywords
Confidence Intervals, Decision Making, Humans, Odds Ratio, Periodicals as Topic/standards, Reference Standards, Sensitivity and Specificity, Stochastic Processes
Pubmed
Web of science
Create date
08/09/2011 15:08
Last modification date
20/08/2019 13:17
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