The Practical Alternative to the <i>p</i> Value Is the Correctly Used <i>p</i> Value

Lakens, Daniël

doi:10.1177/1745691620958012

Cited by 76 publications

(57 citation statements)

References 72 publications

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“…Instead, many manuscripts, especially those without hypothesis tests, can adopt a continuous and unconditional interpretation of statistics (Rafi & Greenland, 2020). Studies that are exploratory, or at least not focused on hypothesis tests, should spend more time describing the statistical results within the manuscript and avoid placing emphasis on statistical significance, or at least, make the correct use of p-values in informing their decisions (Lakens, 2021). Generally, we recommend that sport and exercise scientists adopt a more diverse set of statistical tools and for journals to encourage manuscript submissions that do not rely only upon significance testing to inform decisions.…”

Section: Discussionmentioning

confidence: 99%

Nature of Our Literature

Twomey

Yingling

Warne

et al. 2021

Commun in Kinesiology

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Scientists rely upon an accurate scientific literature in order to build and test new theories about the natural world. In the past decade, observational studies of the scientific literature have indicated that numerous questionable research practices and poor reporting practices may be hindering scientific progress. In particular, 3 recent studies have indicated an implausibly high rate of studies with positive (i.e., hypothesis confirming) results. In sports medicine, a field closely related to kinesiology, studies that tested a hypothesis indicated support for their primary hypothesis ~70% of the time. However, a study of journals that cover the entire field of kinesiology has yet to be completed, and the quality of other reporting practices, such as clinical trial registration, has not been evaluated. In this study we retrospectively evaluated 300 original research articles from the flagship journals of North America (Medicine and Science in Sports and Exercise), Europe (European Journal of Sport Science), and Australia (Journal of Science and Medicine in Sport). The hypothesis testing rate (~64%) and positive result rate (~81%) were much lower than what has been reported in other fields (e.g., psychology), and there was only weak evidence for our hypothesis that the positive result rate exceeded 80%. However, the positive result rate is still considered unreasonably high. Additionally, most studies did not report trial registration, and rarely included accessible data indicating rather poor reporting practices. The majority of studies relied upon significance testing (~92%), but it was more concerning that a majority of studies (~82%) without a stated hypothesis still relied upon significance testing. Overall, the positive result rate in kinesiology is unacceptably high, despite being lower than other fields such as psychology, and most published manuscripts demonstrated subpar reporting practices

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Section: Discussionmentioning

confidence: 99%

Nature of Our Literature

Twomey

Yingling

Warne

et al. 2021

Commun in Kinesiology

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“…Importantly, only the block permutation test provides a uniform distribution and hence a valid p-value. Altman and Krzywinski, 2017;Amrhein et al, 2019;Lakens, 2021). This is mainly due to misinterpretations of how to correctly interpret p-values.…”

Section: Discussionmentioning

confidence: 99%

Don’t Be Fooled by Randomness: Valid p-Values for Single Molecule Microscopy

Schneider

Schütz

2022

Front. Bioinform.

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The human mind shows extraordinary capability at recognizing patterns, while at the same time tending to underestimate the natural scope of random processes. Taken together, this easily misleads researchers in judging whether the observed characteristics of their data are of significance or just the outcome of random effects. One of the best tools to assess whether observed features fall into the scope of pure randomness is statistical significance testing, which quantifies the probability to falsely reject a chosen null hypothesis. The central parameter in this context is the p-value, which can be calculated from the recorded data sets. In case of p-values smaller than the level of significance, the null hypothesis is rejected, otherwise not. While significance testing has found widespread application in many sciences including the life sciences, it is hardly used in (bio-)physics. We propose here that significance testing provides an important and valid addendum to the toolbox of quantitative (single molecule) biology. It allows to support a quantitative judgement (the hypothesis) about the data set with a probabilistic assessment. In this manuscript we describe ways for obtaining valid p-values in two selected applications of single molecule microscopy: (i) Nanoclustering in single molecule localization microscopy. Previously, we developed a method termed 2-CLASTA, which allows to calculate a valid p-value for the null hypothesis of an underlying random distribution of molecules of interest while circumventing overcounting issues. Here, we present an extension to this approach, yielding a single overall p-value for data pooled from multiple cells or experiments. (ii) Single molecule trajectories. Data from a single molecule trajectory are inherently correlated, thus prohibiting a direct analysis via conventional statistical tools. Here, we introduce a block permutation test, which yields a valid p-value for the analysis and comparison of single molecule trajectory data. We exemplify the approach based on FRET trajectories.

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“…The chi-square test ( χ 2 ) was used to determine the differences between the compared groups. Being aware of the ongoing p -value debate and its importance in revealing the significance of a relationship or effect (Maula and Wouter, 2020; Lakens, 2021), we decided to present its value, which may still be of practical importance (Di Leo and Sardanelli, 2020). Therefore, the following terms were used to determine the significance level of the identified relationships or differences ( p values): p ≥ 0.05 as a statistically nonsignificant value and p < 0.05 as a statistically significant value.…”

Section: Methodsmentioning

confidence: 99%

Enterprises' perception and practice of humane entrepreneurship

Dębicka

Olejniczak

Skąpska

2021

JSBED

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PurposeAs a new concept for humane entrepreneurship (HumEnt) evolves, many new research questions arise. At the exploratory stage, the authors found it relevant to examine and discuss the perception of the fundamental assumptions of the HumEnt concept and activities undertaken in this area by business practice.Design/methodology/approachTo thoroughly understand the studied phenomenon, a combination of quantitative and qualitative methods was used. An exploratory survey was obtained from 126 purposefully selected enterprises in Poland; then, a single case study was analysed.FindingsThe conducted analysis showed differences between the activities of enterprises and the perception of the HumEnt concept among employees that are especially noticeable at different levels of the management hierarchy.Research limitations/implicationsThe multifaceted nature of the results obtained is limited by the inability to infer international differences, to capture trends over time and to generalise to the total population of enterprises.Practical implicationsAlthough the surveyed companies recognise the importance of the HumEnt concept, it is not tantamount to its execution. The research results may be valuable, especially for smaller enterprises, where the business practice may require support in applying the HumEnt approach.Originality/valueThe research explored both the actual state confirmed by the actions taken and the perception of the importance of individual elements of HumEnt. A knowing–doing gap has been demonstrated between these planes. Moreover, thanks to a two-stage study, practices were selected that can be successfully implemented also in small and medium-sized enterprises.

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The Practical Alternative to the p Value Is the Correctly Used p Value

Cited by 76 publications

References 72 publications

Nature of Our Literature

Nature of Our Literature

Don’t Be Fooled by Randomness: Valid p-Values for Single Molecule Microscopy

Enterprises' perception and practice of humane entrepreneurship

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