Do Statistical Methods Replace Reasoning in Exercise Science Research? How to Avoid Statistics Becoming Merely a Solution in Search of a Problem

2019 ◽  
Author(s):  
Aaron R Caldwell ◽  
Andrew David Vigotsky ◽  
Greg Nuckols ◽  
Ian Boardley ◽  
Julia Schmidt ◽  
...  

The primary means for disseminating sport and exercise science research is currently through journal articles. However, not all studies, especially those with null findings, make it to formal publication. This publication bias towards positive findings may contribute to questionable research practices. Preregistration is a solution to prevent the publication of distorted evidence resulting from this system. This process asks authors to register their hypotheses and methods before data collection on a publicly available repository or by submitting a Registered Report. In the Registered Reports format, authors submit a Stage 1 manuscript to a participating journal that includes an introduction, methods, and any pilot data indicating the exploratory or confirmatory nature of the study. After a Stage 1 peer review, the manuscript can then be offered in-principle acceptance, rejected, or sent back for revisions to improve the quality of the study. If accepted, the project is guaranteed publication, assuming the authors follow the data collection and analysis protocol. After data collection, authors re-submit a Stage 2 manuscript that includes the results and discussion, and the study is evaluated on clarity and conformity with the planned analysis. In its final form, Registered Reports appear almost identical to a typical publication, but give readers confidence that the hypotheses and main analyses are less susceptible to bias from questionable research practices. From this perspective, we argue that inclusion of Registered Reports by researchers and journals will improve the transparency, replicability, and trust in sport and exercise science research.


Author(s):  
Emma S. Cowley ◽  
Alyssa A. Olenick ◽  
Kelly L. McNulty ◽  
Emma Z. Ross

This study aimed to conduct an updated exploration of the ratio of male and female participants in sport and exercise science research. Publications involving humans were examined from The European Journal of Sports Science, Medicine & Science in Sport & Exercise, The Journal of Sport Science & Medicine, The Journal of Physiology, The American Journal of Sports Medicine, and The British Journal of Sports Medicine, 2014–2020. The total number of participants, the number of male and female participants, the title, and the topic, were recorded for each publication. Data were expressed in frequencies and percentages. Chi-square analyses were used to assess the differences in frequencies in each of the journals. About 5,261 publications and 12,511,386 participants were included in the analyses. Sixty-three percentage of publications included both males and females, 31% included males only, and 6% included females only (p < .0001). When analyzing participants included in all journals, a total of 8,253,236 (66%) were male and 4,254,445 (34%) were female (p < .0001). Females remain significantly underrepresented within sport and exercise science research. Therefore, at present most conclusions made from sport and exercise science research might only be applicable to one sex. As such, researchers and practitioners should be aware of the ongoing sex data gap within the current literature, and future research should address this.


2020 ◽  
Vol 38 (17) ◽  
pp. 1933-1935 ◽  
Author(s):  
Grant Abt ◽  
Colin Boreham ◽  
Gareth Davison ◽  
Robin Jackson ◽  
Alan Nevill ◽  
...  

2017 ◽  
Vol 54 (1) ◽  
pp. 43-59
Author(s):  
Bogna Zawieja ◽  
Bartłomiej Glina

Summary In studies of organic soil degradation and transformation, alongside the conventional methods used in soil science, an increase in the importance of advanced statistical methods can be observed. In this study some multivariate statistical methods were applied in an investigation of organic soil transformation in the central Sudetes. Andrews curves, linear and kernel discriminant variable analysis and cluster analysis were used. The similarities among peatland soils and their layers were determined. It can be stated that the application of statistical methods in soil science research related to organic soil transformation is a valuable tool. The use of various statistical methods (such as Andrews curves, linear and kernel discriminant variables and cluster analysis) can with high probability confirm earlier laboratory or field observations. This is particularly justified in the case of organic soils derived from varied geobotanical peat materials, different types of peatlands and water supply types, which impact the primary properties of the soil.


Sign in / Sign up

Export Citation Format

Share Document