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Herwibawa
Calcite | Level 5

My experiment arranged in Split Plot design. How to make a Charts/ Boxplots for Proportions of a Binary Variable ?

data Survival;

  input A $ B $ Block Y;  if Y=1 then 1='Survive'; else 0='Died';

datalines;

A1     B1     1      0

A1     B1     2      1

A1     B1     3      0

A1     B1     4      0

A1     B1     5      0

A1     B2     1      1

A1     B2     2      1

A1     B2     3      1

A1     B2     4      1

A1     B2     5      0

A1     B3     1      1

A1     B3     2      0

A1     B3     3      0

A1     B3     4      1

A1     B3     5      1

A2     B1     1      0

A2     B1     2      0

A2     B1     3      0

A2     B1     4      0

A2     B1     5      0

A2     B2     1      1

A2     B2     2      0

A2     B2     3      0

A2     B2     4      1

A2     B2     5      0

A2     B3     1      1

A2     B3     2      1

A2     B3     3      1

A2     B3     4      0

A2     B3     5      1

A3     B1     1      1

A3     B1     2      0

A3     B1     3      1

A3     B1     4      0

A3     B1     5      0

A3     B2     1      0

A3     B2     2      1

A3     B2     3      1

A3     B2     4      1

A3     B2     5      0

A3     B3     1      0

A3     B3     2      1

A3     B3     3      0

A3     B3     4      1

A3     B3     5      1

;

 

Is it true when it displayed in as shown below ? how to write the codes?

 

original.jpg

 

 

Please help me it is so important for me...

1 REPLY 1
Rick_SAS
SAS Super FREQ

I assume you know how to model the data to obtain the probabilities, and that you are asking about how to create the box plot of the results.

 

You don't mention what version of SAS you are running, but here's how to create the plot in the current version:

 

data Sim;
label p = "Survival Probability (%)";
call streaminit(1);
do i = 1 to 20;
   Genotype = 1;  Status = "Perishing";
   p = rand("normal", 32, 10) / 100;
   output;
   Genotype = 1;  Status = "Surviving";
   p = rand("normal", 72, 5) / 100;
   output;
   Genotype = 2;  Status = "Perishing";
   p = rand("normal", 32, 10) / 100;
   output;
   Genotype = 2;  Status = "Surviving";
   p = rand("normal", 74, 8) / 100;
   output;
end;
run;

proc sgplot data=Sim;
format p PERCENT8.; vbox p / category=Genotype group=Status nofill nooutliers groupdispay=overlay; scatter y=p x=Genotype / group=Status; run;

 

One question you might have is when to use CATEGORY= and when to use GROUP=. For an explanation, see the article "What is the difference between categories and groups in PROC SGPLOT?"


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