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About 10,000 papers for “Significant difference”

No Significant Difference

David Penrose · Bulletin of Miscellaneous Information (Royal Gardens Kew)

This is the recent podcast for That's Podutainment. Is there a difference between online learning and face-to-face learning?

Cited by 0

minimum significant difference

2025

Citation: 'minimum significant difference' in the IUPAC Compendium of Chemical Terminology, 5th ed.; International Union of Pure and Applied Chemistry; 2025. Online version 5.0.0, 2025. 10.1351/goldbook.14857 • License: The IUPAC Gold Book is licensed under Creative Commons Attribution-ShareAlike CC BY-SA 4.0 International for individual terms. Requests for commercial usage of the compendium should be directed to IUPAC.

Cited by 0

'No Statistically Significant Difference'

William M. Bourne · Archives of Ophthalmology · 1987

In many scientific communications, we are confronted with data showing "no statistically significant difference" between two groups (populations) with respect to a certain variable. The authors often conclude that the two groups are not different regarding that variable. Such a conclusion is not warranted without an indication of the<i>power</i>of the statistical test to detect a<i>clinically important difference</i>. In reality, the two groups referred to almost certainly are at least minutely different. However, whether or not the difference will lead to a statistically significant difference between samples in the study depends on the following: (1) the variability of the variable in the population (which can be estimated using the standard deviation of the same or similar data), (2) the sample size (the number of independent subjects or data points in the samples from each group), and (3) the chosen level of significance (the probability that any difference found

Cited by 16

Minimum Significant Difference (MSD)

Monica Nordberg, Douglas M. Templeton, Ole Andersen et al. · IUPAC Standards Online · 2016

The objective of the “Glossary of terms used in ecotoxicology” is to give clear definitions for those who contribute to studies relevant to ecotoxicology but are not themselves ecotoxicologists. This objective applies especially to chemists who need to understand the ecotoxicological literature without recourse to a multiplicity of dictionaries. The glossary includes terms related to chemical speciation in the environment, sampling, monitoring, and environmental analysis, as well as to adverse ecological effects of chemicals, ecological biomarkers, and the environmental distribution of chemicals. The dictionary consists of about 1139 terms. The authors hope that among the groups who will find this glossary helpful, in addition to chemists, are pharmacologists, toxicologists, ecotoxicologists, risk assessors, regulators, medical practitioners, and regulatory authorities. In particular, the glossary should facilitate the use of chemistry in relation to environmental risk assessment.

Cited by 0Open access

EXPLANATION OF SIGNIFICANT DIFFERENCE

Epa Superfund, Salem Acres, John F. Kennedy et al. · 1997

Under Section 117 (a) of the Comprehensive Environmental Response, Compensation and Liability Act (CERCLA), and promulgated in 40 C.F.R. Sections 300.435(c)(2)(I)and 300.825(a)(2), if the United States Environmental Protection Agency (EPA) determines that the remedial action at the Site differs significantly in scope performance or cost from the Record of Decision (ROD) for the Site, EPA shall publish an explanation of significant difference between the remedial action being undertaken and the remedial action set forth in the ROD and the reasons such changes are being made. This Explanation of Significant Difference (ESD) contains a brief history of the Salem Acres Site, a description of the remedy selected in the ROD signed on March 25,1993, and a description of and rationale for the change to the ROD. This ESD and other supporting documents can be found in the Administrative Record located at EPA&amp;apos;s Region I

Cited by 0

EDITORIAL No Significant Difference...Says

2008

of the meaning and importance of P values in the medical literature. As readers of the literature, many of us too often merely look at the results of a trial and take the authors at their word regarding the statistical significance of their findings. Dr. Cloft’s main point was that, as readers, we need to critically evaluate the findings that are being presented to us. Not only do we need to consider the questions that Dr. Cloft posed for positive statistical findings (Why should I care? Is the result consistent with my experience? Were the right tests and the right numbers used?) but also we need to equally critically evaluate negative findings. If an author tells us that there was no significant difference between groups, should we believe it? This depends on many issues and raises the question of statistical power. P values describe the risk of making a type I error (�) (that

Cited by 0

The significant difference in impact

Wennström, Sofie, Schubert, Gabor, Stone, Graham et al. · JISC Information Environment Repository (Jisc) · 2019

This paper analyses usage statistics, citation data and altmetrics from a university press publishing open access monographs. The bibliometric data is then contrasted to the outcome of a survey of attitudes and behaviour among authors and editors who have published open access books. The metrics indicate that downloads and citations depend on the community of practice of the intended audience within each specific academic discipline, as well as the content itself. There is, for example, a clear difference in usage patterns between monographs and anthologies. The altmetric data used in the study indicate how users interact with the published books online. The data suggests, despite the small sample, that authors can to a greater extent influence how their book is discovered by the readership. It would, therefore, be relevant for authors to become more aware of the type of metrics available and how they can be interpreted and used for better understanding of how the book can reach its intended audience. Further studies are needed, and publishers of open access books are encouraged to share data for benchmarking and development of best practices. &#13;\n&#13;\nELPUB 2019 23rd edition of the International Conference on Electronic Publishing, Jun 2019, Marseille,&#13;\nFrance. hal-02141879&#13;\n&#13;\nhttps://hal.archives-ouvertes.fr/hal-02141879&#13;\n&#13;\n

Cited by 0Open access

No significant difference ... Says who?

Andrew T. Trout, Timothy J. Kaufmann, David F. Kallmes · PubMed · 2007

In the August 2006 issue of AJNR , Dr. Cloft presented a discussion of the meaning and importance of P values in the medical literature. As readers of the literature, many of us too often merely look at the results of a trial and take the authors at their word regarding the statistical significance

Cited by 14Open access

The Difference Between “Significant” and “Not Significant” is not Itself Statistically Significant

Andrew Gelman, Hal S. Stern · The American Statistician · 2006

It is common to summarize statistical comparisons by declarations of statistical significance or nonsignificance. Here we discuss one problem with such declarations, namely that changes in statistical significance are often not themselves statistically significant. By this, we are not merely making the commonplace observation that any particular threshold is arbitrary—for example, only a small change is required to move an estimate from a 5.1% significance level to 4.9%, thus moving it into statistical significance. Rather, we are pointing out that even large changes in significance levels can correspond to small, nonsignificant changes in the underlying quantities.The error we describe is conceptually different from other oft-cited problems—that statistical significance is not the same as practical importance, that dichotomization into significant and nonsignificant results encourages the dismissal of observed differences in favor of the usually less interesting null hypothesis of no difference, and that any particular threshold for declaring significance is arbitrary. We are troubled by all of these concerns and do not intend to minimize their importance. Rather, our goal is to bring attention to this additional error of interpretation. We illustrate with a theoretical example and two applied examples. The ubiquity of this statistical error leads us to suggest that students and practitioners be made more aware that the difference between “significant” and “not significant” is not itself statistically significant.

Cited by 1,192

Significant group difference in GM volume.

Eva Blix (420252), Aleksander Perski (305801), Hans Berglund (367020) et al. · Figshare · 2015

&lt;p&gt;# Cluster showing a significant group difference when using a limbic mask comprising the anterior cingulate cortex, the mPFC, the insular cortex, the hippocampus and the amygdala, using peak threshold at p = 0.001, FDR corrected at p&lt;0.05. The other clusters were calculated with same level of significance, but using the entire brain as search space (no a priori hypothesis).&lt;/p&gt;&lt;p&gt;No group differences were observed in white matter volumes and no significant clusters were detected when reversing the contrast (using the contrast: stressed patients – controls).&lt;/p&gt;

Cited by 0Open access

The Significance of ‘No Significant Difference’

J. Brismar, Bo Jacobsson · Acta Radiologica · 1990

It is generally accepted that patients experience less discomfort with low osmolality contrast media (LOM) than with high osmolar media (HOM). Hard statistical facts from so called 'high quality' controlled trials, proving that more significant reactions such as vomiting, hives, urticaria or anaphylactic complications also are less common with LOM are, however, not readily available (3). One reason for this may be that most of the well designed controlled studies performed may have been tailored by the drug manufacturer for a specific purpose: to fulfil the format requirements for registration by the licensing governmental authorities. For this the sponsor, to save time, usually engages several medical centres, each only performing 15 to 60 studies (4). Materials of such a size are of course much too small to reveal any change in the frequency of a complication occurring with an incidence of only a few per cent or less. The absence of a statistically significant difference in such low incidences of complications does not justify any conclusion. The question then arises: how big a material would be needed to obtain a fair chance to statistically verify a clinically highly important decrease in the incidence of a complication from, for instance, 10 to 5 per cent? This paper deals with such questions.

Cited by 0