
ROSE PLOTName:
According to Wainer (1997), the use of a common angle is the strength of the rose plot since it allows us to easily compare a sequence of rose plots (i.e., the corresponding segments in different rose plots are always in the same relative position). In particular, this makes rose plots an effective technique for displaying the data in contingency tables. Friendly (2000) refers to the special case of 2x2 tables as the fourfold plot. As with the general case, an effective use of these plots is when we have a sequence of related 2x2 tables. Using the MULTIPLOT command, Dataplot can easily generate the sequence of rose plots or fourfold plots on a single page. As an interesting historical note, Wainer points out that rose plots were used by Florence Nightingale (she referred to them as coxcombs).
where <x> is the variable containing counts; and where the <SUBSET/EXCEPT/FOR qualification> is optional. Use this syntax when you have a single variable of counts (or proportions).
where <y1> is the first response variable; <y2> is the second response variable; and where the <SUBSET/EXCEPT/FOR qualification> is optional. With this syntax, the <y1> and <y2> variables are crosstabulated to generate a 2x2 table. The rose plot is then generated from this 2x2 table.
ROSE PLOT X SUBSET TAG > 2 ROSE PLOT Y1 Y2
Friendly (2000), Visualizing Categorical Data SAS Institute Inc., p. 90.
let y = data 48 12 53 7 . region fill on on on on region fill color black blue red green rose plot y . case asis justification left move 15 90 text Truecr()Positives move 15 10 text Falsecr()Positives move 75 90 text Falsecr()Negatives move 75 10 text Truecr()Negatives Program 2: let n = 1 let x = sequence 1 100 1 5 . let p = 0.8 let y1 = binomial rand numb for i = 1 1 100 let p = 0.92 let y2 = binomial rand numb for i = 1 1 100 . let p = 0.6 let y1 = binomial rand numb for i = 101 1 200 let p = 0.95 let y2 = binomial rand numb for i = 101 1 200 . let p = 0.96 let y1 = binomial rand numb for i = 201 1 300 let p = 0.98 let y2 = binomial rand numb for i = 201 1 300 . let p = 0.3 let y1 = binomial rand numb for i = 301 1 400 let p = 0.2 let y2 = binomial rand numb for i = 301 1 400 . let p = 0.9 let y1 = binomial rand numb for i = 401 1 500 let p = 0.2 let y2 = binomial rand numb for i = 401 1 500 . region fill on on on on region color black blue red green rose plot y1 y2 subset x = 5 . set conditioning plot type two variable rose region fill off on on on on region color white black blue red green condition plot y1 y2 x Program 3: orientation square . . Berkeley Admissions Data from p. 391 of . Friendly (2000), "Visualizing Categorical Data", . SAS Institute Inc. . read y1 y2 x 512 313 1 353 207 1 89 19 2 17 8 2 120 205 3 138 279 3 202 391 4 131 244 4 53 138 5 22 351 5 94 299 6 24 317 6 end of data . multiplot corner coordinates 0 0 100 95 multiplot scale factor 2 multiplot 3 3 . legend case asis legend justification left legend 2 justification right legend 4 justification right legend 1 coordinates 17 83 legend 2 coordinates 83 83 legend 3 coordinates 17 22 legend 4 coordinates 83 22 . region fill on on on on region fill color black blue red green box shadow hw 0 0 . label case asis title case asis y1label Admit = Yes y2label Admit = No x1label Sex: Female x2label Sex: Male x2label displacement 74 . let string t1 = Department A let string t2 = Department B let string t3 = Department C let string t4 = Department D let string t5 = Department E let string t6 = Department F . let icnt = 0 let icnt2 =0 loop for k = 1 1 6 let icnt = icnt+1 let atemp = y1(icnt) legend 1 ^atemp let atemp = y2(icnt) legend 2 ^atemp let icnt = icnt+1 let atemp = y1(icnt) legend 3 ^atemp let atemp = y2(icnt) legend 4 ^atemp title ^t^k let icnt2 = icnt2 + 1 if k = 3 let icnt2 = icnt2 + 1 end of if if k = 5 let icnt2 = icnt2 + 1 end of if multiplot 3 3 icnt2 rose plot y1 y2 subset x = k box 15 20 85 90 end of loop . end of multiplot . case asis justification center move 30 97 text Rose Plots for Berkeley Admissions Data
 
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Date created: 1/7/2008 