Call to increase statistical collaboration in sports science, sport and exercise medicine and sports physiotherapy

Kristin L Sainani, David N Borg, Aaron R Caldwell, Michael L Butson, Matthew S Tenan, Andrew J Vickers, Andrew D Vigotsky, John Warmenhoven, Robert Nguyen, Keith R Lohse, Emma J Knight, Norma Bargary, Kristin L Sainani, David N Borg, Aaron R Caldwell, Michael L Butson, Matthew S Tenan, Andrew J Vickers, Andrew D Vigotsky, John Warmenhoven, Robert Nguyen, Keith R Lohse, Emma J Knight, Norma Bargary

No abstract available

Keywords: methodology; statistical review; statistics.

Conflict of interest statement

Competing interests: None declared.

Figures

Figure 1
Figure 1
Flowchart of the article search and inclusion for the systematic review.
Figure 2
Figure 2
Percentage of data-containing articles in quartile one sports science journals that include at least one coauthor affiliated with a statistics or other methodologically-oriented department (from our systematic review, n=299). Statistics includes biostatistics, statistics, data science and data analytics departments; epidemiology includes authors from departments of community health, population health, health or public health if they are trained as epidemiologists or statisticians; computer science includes information technology department.

References

    1. Scales CD, Norris RD, Peterson BL, et al. . Clinical research and statistical methods in the urology literature. J Urol 2005;174:1374–9. 10.1097/01.ju.0000173640.91654.b5
    1. Strasak AM, Zaman Q, Pfeiffer KP, et al. . Statistical errors in medical research--a review of common pitfalls. Swiss Med Wkly 2007;137:44–9.
    1. Schatz P, Jay KA, McComb J, et al. . Misuse of statistical tests in Archives of clinical neuropsychology publications. Arch Clin Neuropsychol 2005;20:1053–9. 10.1016/j.acn.2005.06.006
    1. George BJ, Beasley TM, Brown AW, et al. . Common scientific and statistical errors in obesity research. Obesity 2016;24:781–90. 10.1002/oby.21449
    1. Ercan I. Examining of published articles with respect to statistical errors in medical sciences. UHOD 2015;25:130–8. 10.4999/uhod.15942
    1. Knudson D. Statistical and reporting errors in applied biomechanics research. In: ISBS - Conference Proceedings Archive. Beijing, China, 2008. Available:
    1. Kim Y, Lee JL. Common mistakes in statistical and methodological practices of sport management research. Meas Phys Educ Exerc Sci 2019;23:314–24. 10.1080/1091367X.2018.1537278
    1. Nielsen RO, Chapman CM, Louis WR, et al. . Seven SINS when interpreting statistics in sports injury science. Br J Sports Med 2018;52:1410–2. 10.1136/bjsports-2017-098524
    1. Schweizer G, Furley P. Reproducible research in sport and exercise psychology: the role of sample sizes. Psychol Sport Exerc 2016;23:114–22. 10.1016/j.psychsport.2015.11.005
    1. Nevill AM, Holder RL, Cooper S-M. Statistics, truth, and error reduction in sport and exercise sciences. Eur J Sport Sci 2007;7:9–14. 10.1080/17461390701197767
    1. Halperin I, Vigotsky AD, Foster C, et al. . Strengthening the practice of exercise and Sport-Science research. Int J Sports Physiol Perform 2018;13:127–34. 10.1123/ijspp.2017-0322
    1. Tabb M. Inside the weird world of online fitness advice that’s hard to debunk with real science. Quartz, 2019. Available: [Accessed 7 Mar 2020].
    1. Aschwanden C, Nguyen M. How Shoddy Statistics Found a Home in Sports Research. FiveThirtyEight. Accessed (March 7, 2020).
    1. Mannix L. Cold water poured on scientific studies based on statistical cult. The Sydney morning herald. Available: [Accessed 7 Mar 2020].
    1. Simmons JP, Nelson LD, Simonsohn U. False-Positive psychology: undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychol Sci 2011;22:1359–66. 10.1177/0956797611417632
    1. Open Science Collaboration Psychology. estimating the reproducibility of psychological science. Science 2015;349:aac4716. 10.1126/science.aac4716
    1. John LK, Loewenstein G, Prelec D. Measuring the prevalence of questionable research practices with incentives for truth telling. Psychol Sci 2012;23:524–32. 10.1177/0956797611430953
    1. Nosek BA, Spies JR, Motyl M. Scientific utopia: II. restructuring incentives and practices to promote truth over Publishability. Perspect Psychol Sci 2012;7:615–31. 10.1177/1745691612459058
    1. Casals M, Finch CF. Sports Biostatistician: a critical member of all sports science and medicine teams for injury prevention. Inj Prev 2017;23:423–7. 10.1136/injuryprev-2016-042211
    1. Casals M, Nielsen RO. Who and what can contribute to improve the statistical thinking in sports injury research? A humorous analogy between basketball and members of the multidisciplinary research team. Apunts. Medicina de l'Esport 2019;54:81–4. 10.1016/j.apunts.2019.09.002
    1. Nielsen RO, Shrier I, Casals M, et al. . Statement on methods in sport injury research from the 1st methods matter meeting, Copenhagen, 2019. Br J Sports Med 2020;54:941. 10.1136/bjsports-2019-101323
    1. Box GEP. Science and statistics. J Am Stat Assoc 1976;71:791–9. 10.1080/01621459.1976.10480949
    1. Stark PB, Saltelli A. Cargo-cult statistics and scientific crisis. Significance 2018;15:40–3. 10.1111/j.1740-9713.2018.01174.x
    1. Gigerenzer G. Statistical rituals: the replication delusion and how we got there. Adv Methods Pract Psychol Sci 2018;1:198–218. 10.1177/2515245918771329
    1. Batterham AM, Hopkins WG. Making meaningful inferences about magnitudes. Int J Sports Physiol Perform 2006;1:50–7. 10.1123/ijspp.1.1.50
    1. Cleather D. On the use and abuse of principal component analysis in biomechanics. SportRxiv 2019.
    1. Dankel SJ, Loenneke JP. A method to stop analyzing random error and start analyzing differential responders to exercise. Sports Med 2020;50:231–8. 10.1007/s40279-019-01147-0
    1. Welsh AH, Knight EJ. "Magnitude-based inference": a statistical review. Med Sci Sports Exerc 2015;47:874–84. 10.1249/MSS.0000000000000451
    1. Tenan MS, Vigotsky AD, Caldwell AR. Comment on: "A Method to Stop Analyzing Random Error and Start Analyzing Differential Responders to Exercise". Sports Med 2020;50:431–4. 10.1007/s40279-019-01249-9
    1. Ogden HB, Fallowfield JL, Child RB, et al. . Reliability of gastrointestinal barrier integrity and microbial translocation biomarkers at rest and following exertional heat stress. Physiol Rep 2020;8:e14374. 10.14814/phy2.14374
    1. Łagowska K. The relationship between vitamin D status and the menstrual cycle in young women: a preliminary study. Nutrients 2018;10:1729. 10.3390/nu10111729
    1. MARS Group, Wright RW, Huston LJ, et al. . Predictors of patient-reported outcomes at 2 years after revision anterior cruciate ligament reconstruction. Am J Sports Med 2019;47:2394–401. 10.1177/0363546519862279
    1. Tenan MS, Simon JE. Predictors of patient-reported outcomes at 2 years after revision anterior cruciate ligament reconstruction: letter to the editor. Am J Sports Med 2020;48:NP31–2. 10.1177/0363546520903674
    1. Wright RW, Huston LJ, Nwosu S. Predictors of patient-reported outcomes at 2 years after revision anterior cruciate ligament reconstruction: response. Am J Sports Med 2020;48:NP32. 10.1177/0363546520903676
    1. Tusher VG, Tibshirani R, Chu G. Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci U S A 2001;98:5116–21. 10.1073/pnas.091062498
    1. Senn S. Mastering variation: variance components and personalised medicine. Stat Med 2016;35:966–77. 10.1002/sim.6739
    1. Bamman MM, Petrella JK, Kim J-su, et al. . Cluster analysis tests the importance of myogenic gene expression during myofiber hypertrophy in humans. J Appl Physiol 2007;102:2232–9. 10.1152/japplphysiol.00024.2007
    1. Damas F, Barcelos C, Nóbrega SR, et al. . Individual muscle hypertrophy and strength responses to high vs. low resistance training frequencies. J Strength Cond Res 2019;33:897–901. 10.1519/JSC.0000000000002864
    1. Tenan M. Why — even after reforms for an episode involving bad statistics — is it so difficult to correct the sports medicine literature? Retraction watch, 2020. Available: [Accessed 16 Mar 2020].
    1. Ramsay JO, Silverman BW. Applied functional data analysis: methods and case studies. Springer, 2002.
    1. Warmenhoven J, Cobley S, Draper C, et al. . Considerations for the use of functional principal components analysis in sports biomechanics: examples from on-water rowing. Sports Biomech 2019;18:317–41. 10.1080/14763141.2017.1392594
    1. Donoghue OA, Harrison AJ, Coffey N, et al. . Functional data analysis of running kinematics in chronic Achilles tendon injury. Med Sci Sports Exerc 2008;40:1323–35. 10.1249/MSS.0b013e31816c4807
    1. Donà G, Preatoni E, Cobelli C, et al. . Application of functional principal component analysis in race walking: an emerging methodology. Sports Biomech 2009;8:284–301. 10.1080/14763140903414425
    1. Coffey N, Harrison AJ, Donoghue OA, et al. . Common functional principal components analysis: a new approach to analyzing human movement data. Hum Mov Sci 2011;30:1144–66. 10.1016/j.humov.2010.11.005
    1. Hooker G, 2019. Available: [Accessed 21 Mar 2020].
    1. Barker RJ, Schofield MR. Inference about magnitudes of effects. Int J Sports Physiol Perform 2008;3:547–57. 10.1123/ijspp.3.4.547
    1. Sainani KL. The Problem with "Magnitude-based Inference". Med Sci Sports Exerc 2018;50:2166–76. 10.1249/MSS.0000000000001645
    1. Sainani KL, Lohse KR, Jones PR, et al. . Magnitude‐based inference is not Bayesian and is not a valid method of inference. Scand J Med Sci Sports 2019;29:1428–36. 10.1111/sms.13491
    1. Mengersen KL, Drovandi CC, Robert CP, et al. . Bayesian estimation of small effects in exercise and sports science. PLoS One 2016;11:e0147311. 10.1371/journal.pone.0147311
    1. Butson ML. Will the numbers really love you back: re-examining Magnitude-Based inference. SportRxiv 2017.
    1. Curran-Everett D. Magnitude-based inference: good idea but flawed approach. Med Sci Sports Exerc 2018;50:2164–5. 10.1249/MSS.0000000000001646
    1. Lohse K, Sainani K, Taylor JA, et al. . Systematic Review of the Use of “Magnitude-Based Inference” in Sports Science and Medicine. SportRxiv 2020.
    1. Goodman SN. Why is Getting Rid of P -Values So Hard? Musings on Science and Statistics. Am Stat 2019;73:26–30. 10.1080/00031305.2018.1558111
    1. Ehrlinger J, Johnson K, Banner M, et al. . Why the unskilled are Unaware: further explorations of (absent) Self-Insight among the incompetent. Organ Behav Hum Decis Process 2008;105:98–121. 10.1016/j.obhdp.2007.05.002
    1. Smaldino PE, McElreath R. The natural selection of bad science. R Soc Open Sci 2016;3:160384. 10.1098/rsos.160384
    1. Bancroft TA. What rewards may a statistician expect? Am Stat 1970;24:8.
    1. Dahly DL. Statistical reform. medium, 2019. Available:
    1. Melin G. Pragmatism and self-organization. Res Policy 2000;29:31–40. 10.1016/S0048-7333(99)00031-1
    1. Cummings JN, Kiesler S. Who collaborates successfully?: prior experience reduces collaboration barriers in distributed interdisciplinary research. Proceedings of the ACM 2008 Conference on Computer Supported Cooperative Work - CSCW ’08. San Diego, CA, USA: ACM Press, 2008:437.
    1. Kross S, Peng RD, Caffo BS, et al. . The Democratization of data science education. Am Stat 2020;74:1–7. 10.1080/00031305.2019.1668849
    1. Tomcho TJ, Rice D, Foels R, et al. . Apa's learning objectives for research methods and statistics in practice: a Multimethod analysis. Teach Psychol 2009;36:84–9. 10.1080/00986280902739693

Source: PubMed

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