Beyond Bar and Line Graphs: Time for a New Data Presentation Paradigm

PLoS Biology

Volumn 13, Issue 4, 2015, Pages

  Weissgerber, Tracey L ^a   Milic, Natasa M ^a,b   Winham, Stacey J ^a   Garovic, Vesna D ^a  

^a MAYO CLINIC   (United States)

^b UNIVERSITY OF BELGRADE   (Serbia)

Author keywords

[No Author keywords available]

Indexed keywords

BAR GRAPH; DATA PRESENTATION; DATA PROCESSING; HISTOGRAM; INFORMATION PROCESSING; LINE GRAPH; NOTE; PHYSIOLOGY; PUBLICATION; PUBLISHING; RESEARCH; SAMPLE SIZE; SCIENTIFIC LITERATURE; SYSTEMATIC REVIEW (TOPIC); STATISTICAL ANALYSIS;

DATA INTERPRETATION, STATISTICAL; PUBLISHING;

EID: 84929500859     PISSN: 15449173     EISSN: 15457885     Source Type: Journal    
DOI: 10.1371/journal.pbio.1002128     Document Type: Note

References (15)

1. Cooper RJ, Schriger DL, Close RJ, Graphical literacy: the quality of graphs in a large-circulation journal. Annals of emergency medicine. 2002;40: 317–322. 12192357
2. Schriger DL, Sinha R, Schroter S, Liu PY, Altman DG, From submission to publication: a retrospective review of the tables and figures in a cohort of randomized controlled trials submitted to the British Medical Journal. Annals of emergency medicine. 2006;48: 750–756, 756 e751-721. 16978740
3. Lane DM, Sandor A, Designing better graphs by including distributional information and integrating words, numbers, and images. Psychological methods. 2009;14: 239–257. doi: 10.1037/a0016620 19719360
4. Schriger DL, Arora S, Altman DG The content of medical journal Instructions for authors. Annals of emergency medicine. 2006;48: 743–749, 749 e741-744. 17112938
5. Davies HT, Describing and estimating: use and abuse of standard deviations and standard errors. Hospital medicine. 1998;59: 327–328. 9722376
6. Curran-Everett D, Benos DJ, Guidelines for reporting statistics in journals published by the American Physiological Society. Physiological genomics. 2004;18: 249–251. 15306690
7. Rochon J, Gondan M, Kieser M, To test or not to test: Preliminary assessment of normality when comparing two independent samples. BMC Med Res Methodol. 2012;12: 81. doi: 10.1186/1471-2288-12-81 22712852
8. Kuzon WM, Jr.Urbanchek MG, McCabe S, The seven deadly sins of statistical analysis. Annals of plastic surgery. 1996;37: 265–272. 8883724
9. Bridge PD, Sawilowsky SS, Increasing physicians' awareness of the impact of statistics on research outcomes: comparative power of the t-test and and Wilcoxon Rank-Sum test in small samples applied research. Journal of clinical epidemiology. 1999;52: 229–235. 10210240
10. Micceri T, The unicorn, the normal curve, and other improbable creatures. Psychological Bulletin. 1989;105: 156–166.
11. Nuzzo R, Scientific method: statistical errors. Nature. 2014;506: 150–152. doi: 10.1038/506150a 24522584
12. Erb HN, Changing expectations: Do journals drive methodological changes? Should they? Preventive veterinary medicine. 2010;97: 165–174. doi: 10.1016/j.prevetmed.2010.09.011 20951447
13. Baker D, Lidster K, Sottomayor A, Amor S, Two years later: journals are not yet enforcing the ARRIVE guidelines on reporting standards for pre-clinical animal studies. PLoS Biol. 2014;12: e1001756. doi: 10.1371/journal.pbio.1001756 24409096
14. Eisen JA, Ganley E, MacCallum CJ, Open science and reporting animal studies: who's accountable? PLoS Biol. 2014;12: e1001757. doi: 10.1371/journal.pbio.1001757 24409097
15. Oster RA, Lindsell CJ, Welty LJ, Mazumdar M, Thurston SW, Rahbar MH, et al. Assessing Statistical Competencies in Clinical and Translational Science Education: One Size Does Not Fit All. Clinical and translational science. 2014;8: 32–42. doi: 10.1111/cts.12204 25212569