Graphics and statistics for cardiology: Comparing categorical and continuous variables

Heart

Volumn 102, Issue 5, 2016, Pages 349-355

  Rice, Kenneth ^a   Lumley, Thomas ^b  

^a UNIVERSITY OF WASHINGTON   (United States)

^b UNIVERSITY OF AUCKLAND   (New Zealand)

Author keywords

[No Author keywords available]

Indexed keywords

CARDIOLOGY; COMPUTER PROGRAM; HISTOGRAM; HUMAN; MOSAICISM; PRIORITY JOURNAL; PUBLICATION; QUANTITATIVE ANALYSIS; REVIEW; STATISTICS; SYSTOLIC BLOOD PRESSURE; VISION; ANIMAL; BIOSTATISTICS; COMPUTER GRAPHICS; MEDICAL RESEARCH; METHODOLOGY; PROCEDURES; STATISTICS AND NUMERICAL DATA;

ANIMALS; BIOMEDICAL RESEARCH; BIOSTATISTICS; CARDIOLOGY; COMPUTER GRAPHICS; HUMANS; RESEARCH DESIGN; SOFTWARE;

EID: 84964282750     PISSN: 13556037     EISSN: 1468201X     Source Type: Journal    
DOI: 10.1136/heartjnl-2015-308104     Document Type: Review

References (25)

1. Meyer J, Shamo MK, Gopher D. Information structure and the relative efficacy of tables and graphs. Hum Factors 1999;41:570-87.
2. Gelman A, Pasarica C, Dodhia R. Let's practice what we preach: Turning tables into graphs. Am Stat 2002;56:121-30.
3. Centers for Disease Control and Prevention. National Health and Nutrition Examination Survey Data, 2015. U.S. Department of Health and Human Services. http://www.cdc.gov/nchs/nhanes.htm
4. Tukey J. Exploratory data analysis. Reading: Addison-Wesley, 1977.
5. Hintze JL, Nelson RD. Violin plots: A box plot-density trace synergism. Am Stat 1998;52:181-4.
6. Dawson R. How significant is a boxplot outlier. J Stat Ed 2011;19:1-12.
7. Adler D. vioplot: Violin plot, 2005. R package version 0.2. http://wsopuppenkiste. wiso.uni-goettingen.de/~dadler
8. Cleveland WS, McGill R. Graphical perception: Theory, experimentation, and application to the development of graphical methods. J Am Stat Assoc 1984;79:531-54.
9. Lewis S, Clarke M. Forest plots: Trying to see the wood and the trees. BMJ 2001;322:1479.
10. Armitage P, Berry G, Matthews JN. Statistical methods in medical research. Chichester: John Wiley & Sons, Chapter 12, 2008.
11. Spence I. No humble pie: The origins and usage of a statistical chart. J Ed Behav Stat 2005;30:353-68.
12. Van Belle G, Fisher LD, Heagerty PJ, et al. Biostatistics: A methodology for the health sciences. Vol 519. John Wiley & Sons, Chapter 9, 2004.
13. Chambers JM, Cleveland WS, Kleiner B, et al. Graphical methods for data analysis. Wadsworth, Belmont, CA: Wadsworth International Group, 1984.
14. Few S. Now you see it: Simple visualization techniques for quantitative analysis. Burlingame, CA: Analytics Press, Chapter 5, 2009.
15. Freedman DA. On the so-called "Huber sandwich estimator" and "robust standard errors". Am Stat 2006;60:299-302.
16. Greenland S. Dose-response and trend analysis in epidemiology: Alternatives to categorical analysis. Epidemiology 1995;6:356-65.
17. Cleveland WS. Robust locally weighted regression and smoothing scatterplots. J Am Stat Assoc 1979;74:829-36.
18. Hastie TJ, Tibshirani RJ. Generalized additive models. Vol. 43. Boca Raton, FL: CRC Press, Chapter 2, 1990.
19. Hofmann H. Graphical tools for the exploration of multivariate categorical data. Norderstedt: BoD-Books on Demand, 2001.
20. Unwin A, Hofmann H, Cook D. Let graphics tell the story-datasets in R. R J 2013;5;117-29.
21. Brewer C, Harrower M, Sheesley B, et al. ColorBrewer 2.0, 2015. http://www. colorbrewer2.org/(accessed Jul).
22. Krzywinski M, Wong B. Points of view: Plotting symbols. Nat Methods 2013;10:451.
23. Ellis SR. Pictorial communication: Pictures and the synthetic universe. Leonardo 1990;23:81-6.
24. Nelson L, Cook D, Cruz-Neira C. XGobi vs the C2: Results of an experiment comparing data visualization in a 3-D immersive virtual reality environment with a 2-D workstation display. Comput Stat 1999;14:39-51.
25. Friendly M. Mosaic displays for multi-way contingency tables. J Am Stat Assoc 1994;89:190-200.