Richard A. O'Keefe <[EMAIL PROTECTED]> wrote: > Someone mentioned the new "Diamond Graphs" invented at Johns Hopkins. > I haven't see the August 2003 issue of The American Statistician yet, > but I _have_ read the press release. Same here. > The fact that someone would try to patent this strikes me as outrageous; > the actual amount of novelty is so tiny. Agree again. [Richards points edited for space]
> For R, I don't think it matters, because I think that diamond graphs > are a bad idea. > In short, it looks to me as though "diamond graphs" are something R > is better off without. A few points to add to Richards comments. The proposed "diamond graph" is not innovative, more intuitive, or more accurate than existing graph forms. It is applicable to one limited graphing problem: a continuous (outcome) dimension and two discrete categorical dimensions. Ironically, the example http://www.jhu.edu/~gazette/2003/18aug03/18graph.html uses artificially imposed discrete categories on two continuous variables! Why not treat them as continuous? This specific problem (2 categorical, 1 continuous) presents the challenge of representing 3 dimensions on a two dimensional plane. The "traditional" solution is the "3D bar chart" which uses perspective to represent the third dimension. There are many problems with that compromise. The two greatest being that the fixed perspective can obscure bars further back in the z (depth) dimension, and that perception of the relative size (height) of the bars is less precise due to projection of the third dimension through perspective. The perspective distortion can be corrected through stereoscopic presentation, the obstruction of bars can be corrected through animation. These solutions complete the third dimension, but will not work on a monochromatic printed page. Less expensive and more practical would be to present the data in a two dimensional matrix (as proposed in the "diamond") but not to use an odd shape to convey the third dimension. The third dimension could be represented by hue (color) or brightness (shade). I suspect that actual psychometric tests would show that color or other visual representations of density would be more accurate and reliable than their proposed solution which confounds area with shape. As a caveat, I have not read the American Statistician article. I will be surprised if they present data showing that users can more accurately perceive variation in the continuous variable through their odd shape solution in contrast to either color or shade. Harold Baize, Ph.D. Research and Evaluation Youth Services Division Butte County Department of Behavioral Health [EMAIL PROTECTED] ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help