Sorry Reeza, I do not understand.  ... View more

Thank you. I took off the percent in the x-axis and that's fine but how can I change the name in the key from "mrs_discharge" to "mRS at Discharge"???       ... View more

This is is an improvement but there are few issue. 1) The number for each color is not presented 2) The x-axis should be from 0 to 100%, since we are dealing with row percent. 3) I wish to change mrs_discharge on the key to "mRS at discharge"         ... View more

There are two gropus "Home Discharge" and "IRF Discharge" see table below. For for mRS at discharge equal 0, there were 75 from home discharge and 2 from IRF, so both should have same color . The proportion of the color in both group should be it proportion by group, that is 75/(75+176+ 106 +84+38+11+6) for home  discharge and 2/(2+32+36+59+86+16+8). Similar computation should be done for each mRS discharge by group         mRS at Hospital Discharge Home Discharge IRF Discharge 0  75  2 1  176  32 2  106  36 3  84  59 4  38  86 5  11  16 6  6  8 ... View more

proc format; value mRS_fmt 0 = "mRS 0" 1 = "mRS 1" 2 = "mRS 2" 3 = "mRS 3" 4 = "mRS 4" 5 = "mRS 5" 6 = "mRS 6"; run; proc format; value disposition_fmt 0 = "Home" 3 = "IRF"; run; proc freq data=IRF_sub; table disposition_1*mrs_discharge/ out=summary_data outpct; format mrs_discharge mRS_fmt.; run; title "Discharge mRS by Disposition"; proc sgplot data=summary_data; hbar disposition_1 / group = mrs_discharge response = pct_row stat=pct; *to get counts labelled; hbar disposition_1 / group = mrs_discharge response = count stat=sum seglabel x2axis; x2axis display=none; format disposition_1 disposition_fmt.; run; ... View more

Hello Reeza. I marked this as correct but for some reason the colors in the grotta bar does not match the key below. For home and IRF both should have same color for 0, 1, 2...., 6. Also how do I change the name form mrs_discharge in the key to "mrs at discharge"         ... View more

Both can be used but I like the second plots. So they are both great solutions. ... View more

This is the correct answer:   data random_data; call streaminit(99); do RECORD_NUM = 1 to 100; TYPE = rand("bernoulli", 0.5); mRS = rand('integer', 0, 6); output; end; run; proc format; value mRS_fmt 0 -1 = "mRS 0 - 1" 2 = "mRS 2" 3-5 = "mRS 5" 6 = "mRS 6"; run; proc freq data=random_data; table Type*MRS / out=summary_data outpct; format mRS mRS_fmt.; run; proc sgplot data=summary_data; hbar type / group = mRS response = pct_row stat=pct; *to get counts labelled; hbar type / group = mRS response = count stat=sum seglabel x2axis; x2axis display=none; run; proc sgplot data=random_data; hbar type / group = mRS stat=pct; hbar type / group = mRS stat=freq seglabel x2axis; x2axis display=none; format mRS mRS_fmt.; run; ... View more

This is great! Thanks. ... View more

For instant for type =no, if  88 people had mrs=1, the number 88 will show within the box in the plot, if 7 had mrs=2, the number 2 will appear in corresponding color within the box. That is how the figure above is. You see the sample size within each color, corresponding to the number of people with that mrs value ... View more

That is just part of the data. In the grotta bar graph that I pasted for type "no" we have number 88, 7, 41... How do I have similar plot with different n.?? ... View more

Thank you, this is extremely helpful. How do I put the number into the different shaded regions as in the plot. ... View more

The Hbar statement won't solve it since it will simple have mrs values on the y -axis rather than type ("no" "yes") ... View more

366 data _null_; 367 array _c[5] $16 (5*' '); 368 set stroke end=last; 369 where cmiss(age, gender, race_ethnic, pay_source, cmg_tier, report_cmg, weight_cmg, 369! expected_los)=0; 370 if vvalue(deposi) ~in: _c & i<dim(_c) then do; 371 i+1; 372 _c[i]=vvalue(deposi); 373 end; 374 if last; 375 put (_c[*])(=$hex32. /); 376 run; _c1=20202020202020202020203120202020 _c2=20202020202020202020202020202020 _c3=20202020202020202020202020202020 _c4=20202020202020202020202020202020 _c5=20202020202020202020202020202020 NOTE: There were 230 observations read from the data set WORK.STROKE. WHERE CMISS(age, gender, race_ethnic, pay_source, cmg_tier, report_cmg, weight_cmg, expected_los)=0; NOTE: DATA statement used (Total process time): real time 0.01 seconds cpu time 0.01 seconds ... View more