Plotting question
Well stated, Duncan, and I plead guilty, though I did try to weasel out with caveats. Perhaps I may plead down to a lesser sentence or probation by saying that I was offering what I still believe to be appropriate advice for a general strategy for handling this sort of plotting issue; but that as always, one's mileage may vary depending on the specifics. Extra inline comments below. Cheers, Bert And to return to R, note that any of these options is easy to implement in any of at least 3 different graphics frameworks (base, trellis, and ggplot). So Duncan and I can spar over what we'd like to do without being limited by what software **allows** us to do.
On Mon, Aug 1, 2011 at 1:48 PM, Duncan Murdoch <murdoch.duncan at gmail.com> wrote:
On 11-08-01 11:48 AM, Bert Gunter wrote:
IMHO: On Mon, Aug 1, 2011 at 7:51 AM, Duncan Murdoch<murdoch.duncan at gmail.com> ?wrote:
On 11-08-01 5:44 AM, Andrew McCulloch wrote:
Hi, I use R to draw my graphs. I have 100 points on a simple xy-plot. The points are distinguished by a third variable which is categorical with 10 levels. I have been plotting x against y and using gray scales to distinguish the level of the categorical variable for each point. It looks ok to me but a journal reviewer says this is not any use. I cannot afford to pay for colour prints. Any ideas on what is the best way to distinguish 10 groups on an xy scatter plot?
Plot digits or letters or other symbols. Duncan Murdoch
No, this does not work.
You have amazing perception to know that it doesn't work in Andrew's graph. ?But then you go on to suggest that sometimes it does, and then suggest using symbols. Obviously you need to see the graph to know what works. ?If the 10 categories are ordered, then something like thermometer plots would work. ?If they are grouped into a small number of variations on a small number of groups, then digits or letters combined with shading might work, especially if the groups are well separated, or there are clear patterns. I'd agree with the reviewer than 10 levels of shading is probably too many to distinguish,
But for ordered categories you may not wish to distinguish so much as give an overall gestalt, for which a gray scale with 10 levels could work quite well. So it depends on the specifics of what's being plotted, no? and I'd agree with you that digits 0-9 in equal quantities
in an unstructured scatterplot are probably not a good presentation, but I wouldn't want to give specific advice about plotting a dataset without seeing it. Duncan Murdoch See Cleveland's books (e.g. "Visualizing
Data"). 10 is too many symbols to constantly refer to a legend to keep straight, and digits or letters do not allow you to readily perceive the pattern. (Caveat: If "most" of the data are only 2 or 3 of the symbols, then these can work). I think the OP's idea of using gray scales was better. I would dispute the reviewer and refer them to appropriate references. Alternatively, thermometer plots (aka "filled rectangle" plots) would be best. Again, Cleveland's books provide scientific justification rather than merely the (possibly uninformed) aesthetic opinion of a reviewer. Presumably, the journal editor would accept hard data and psychological research in preference to opinions.
If all else fails I can just remove the graph and give them a table of regression coefficients.
No. I think your attempt to use a graph is a much better way to go. Try to resist poor practices such as just publishing summary statistics. Cheers, Bert
Thanks. Yours Sincerely Andrew McCulloch
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______________________________________________ R-help at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
"Men by nature long to get on to the ultimate truths, and will often be impatient with elementary studies or fight shy of them. If it were possible to reach the ultimate truths without the elementary studies usually prefixed to them, these would not be preparatory studies but superfluous diversions." -- Maimonides (1135-1204) Bert Gunter Genentech Nonclinical Biostatistics