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The cult of statistical significance [PDF]

, 2010
This article takes issue with a recent book by Ziliak and McCloskey (2008) of the same title. Ziliak and McCloskey argue that statistical significance testing is a barrier rather than a booster for empirical research in many fields and should therefore ...
Krämer, Walter
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Paradigma şi prioritatea acesteia în raport cu metoda, în cadrul gândirii statistice

Limbaj si Context, 2009
Statistical thinking is a methodical, comprehensive, simultaneous, and simplifying mind’s process. The significance of a methodical process occurs as a result of this systematic own thinking, complexity is due mainly to the increasingly large statistical
Gheorghe Săvoiu
doaj   +1 more source

Fallacies of Statistical Significance

, 2017
Statistical significance (or hypothesis) tests, and the related concept of p-values, are popular tools in statistical data analysis. Unfortunately, the practical implications of statistical significance often turn out to be limited and are frequently ...
Doganaksoy, Necip, Hahn, Gerald, Meeker, William   +2 more
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Redefine statistical significance [PDF]

, 2018
We propose to change the default P-value threshold for statistical significance from 0.05 to 0.005 for claims of new ...
Camerer, Colin, Benjamin, Daniel J.
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I know what I shouldn’t say, but what should I say? An approach to present results without statistical significance

Frontiers in Applied Mathematics and Statistics
There has been an important move away from the term “statistical significance” in the scientific and statistical community. The desire to “retire 0.05” is rooted in improving scientific reporting by ensuring that researchers report more information than ...
Brian C. Healy, Brian C. Healy, Brian C. Healy   +2 more
doaj   +1 more source

Common pitfalls in statistical analysis: The perils of multiple testing

Perspectives in Clinical Research, 2016
Multiple testing refers to situations where a dataset is subjected to statistical testing multiple times - either at multiple time-points or through multiple subgroups or for multiple end-points. This amplifies the probability of a false-positive finding.
Priya Ranganathan, C S Pramesh, Marc Buyse   +2 more
doaj   +1 more source

Clinical and practical importance versus statistical significance: limitations of conventional statistical inference.

, 2014
Decisions about support for therapies in light of data are made using statistical inference. The dominant approach is null-hypothesis-significance-testing.
Wilkinson, Mick
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Using Dichotomous Variables to Model Structural Changes in Time Series: An Application to International Trade

Engineering Proceedings
This research aimed to elucidate the methodology employed in econometric estimations by utilizing dichotomous variables. These variables served a dual purpose: firstly, they denoted an attribute designed to discern structural changes within a linear ...
Gerardo Covarrubias, Xuedong Liu
doaj   +1 more source

Misinterpreting a Failure to Disconfirm as a Confirmation: A Recurrent Misreading of Significance Tests [PDF]

When a significance test fails to disconfirm a hypothesis economist often interpret this as evidence that this hypothesis is valid. Six such examples are cited from recent journals.
Thomas Mayer
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A Different Statistical Perspective on the Evaluation of Ecological Data Sets

Diversity
Statistical significance varies depending on the sample size. Therefore, when the sample size is sufficient, even differences that affect the total variation very little may be statistically significant.
Soner Yigit
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