Data visualization with SAS programming

How to fix the weights of this forest plot?

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How to fix the weights of this forest plot?

[ Edited ]

I've used the code from here to create a forest plot, and on another question someone kindly gave me some advice on how to change the scale to a non-log one. Unfortunately, I now have a new problem - the size of the weight boxes on the graph doesn't correspond to the pre-computed weights I've listed. Instead, the code is incorrectly calculating new weights/box sizes based on the hedge's g (referred to as 'odds ratio' in the code):

 

Forest_Plot_Vector.gif

--e.g. 3% has two different sizes, 14% is smaller than 4%, etc

 

I've tried modifying the code to avoid that, but either:

 

1. It calculates the correct box size, but not anchored in the correct place: 

 

weight.gif

 

2. It anchors the box in the correct place, but makes all the boxes a uniform size:

 

correct placement.gif

 

Is it possible to amend to the code to anchor the boxes in the right place and make them the correct size?

 

I've been modifying these lines:

 

   /* Compute marker width */                                                                                                           
   x1=oddsratio / (10 ** (weight/2));                                                                                                   
   x2=oddsratio * (10 ** (weight/2));
                                            

And this is the overall code I've been using:

data forest;                                                                                                                            
   input Study $1-18 grp OddsRatio LowerCL UpperCL Weight;                                                                              
   format weight percent5. Q1 Q3 4.2 oddsratio lowercl uppercl 5.3;                                                                     
   ObsId=_N_;                                                                                                                           
   OR='HG'; LCL='LCL'; UCL='UCL'; WT='Weight';                                                                                          
   if grp=1 then do;                                                                                                                    
      weight=weight*.01;                                                                                                                
      Q1=OddsRatio-OddsRatio*weight;                                                                                                    
      Q3=OddsRatio+OddsRatio*weight;                                                                                                    
        lcl2=lowercl;                                                                                                                   
      ucl2=uppercl;                                                                                                                     
   end;                                                                                                                                 
   else study2=study;                                                                                                                   
datalines;                                                                                                                              
Study1               1  -0.170 -0.901 0.560  7                                                                                              
Study2      	     1  0.354	-0.530	1.237 	4                                                                                            
Study3 	             1  -0.204	-1.186	0.779	3                                                                                               
Study4  	     1  -0.848	-1.842	0.146 	3                                                                                               
Study5	    	     1  0.495	-0.179	1.169   8                                                                                               
Study6               1 -0.058	-0.568	0.453  14                                                                                             
Study7               1  0.000	-0.494	0.494  15                                                                                               
Study8               1  0.479	-0.410	1.368 	4                                                                                               
Study9               1  -0.272	-1.335	0.792 	3                                                                                               
Study10              1	 0.227	-0.372	0.827  	10                                                                                                                                                                                     
Overall              2  0.0459 -0.1762 0.222 	 .                                                                                                                                                                                                                                         
;                                                                                                                                       
run;
                                                                                                                                        
proc sort data=forest out=forest2;                                                                                                      
   by descending obsid;                                                                                                                 
run;                                                                                                                                    
                                                                                                                                        
/* Add sequence numbers to each observation */                                                                                       
data forest3;                                                                                                                           
   set forest2 end=last;                                                                                                                
   retain fmtname 'Study' type 'n';                                                                                                     
   studyvalue=_n_;                                                                                                                      
   if study2='Overall' then study2value=1;                                                                                              
   else study2value = .;                                                                                                                
                                                                                                                                        
/* Output values and formatted strings to data set */                                                                                   
   label=study;                                                                                                                         
   start=studyvalue;                                                                                                                    
   end=studyvalue;                                                                                                                      
   output;                                                                                                                              
   if last then do;                                                                                                                     
      hlo='O';                                                                                                                          
      label='Other';                                                                                                                    
   end;                                                                                                                                 
run;                                                                                                                                    
                                                                                                                                        
/* Create the format from the data set */                                                                                                                                                                                                                                      
proc format library=work cntlin=forest3;                                                                                                
run;                                                                                                                                    
                                                                                                                                        
/* Apply the format to the study values and remove Overall from Study column. */                                                        
/* Compute the width of the box proportional to weight in log scale. */                                                                 
data forest4;                                                                                                                           
   format studyvalue study2value study.;                                                                                                
   drop fmtname type label start end hlo pct;                                                                                           
   set forest3 (where=(studyvalue > 0)) nobs=nobs;                                                                                      
   if studyvalue=1 then studyvalue=.;                                                                                                   
   /* Compute marker width */                                                                                                           
   x1=oddsratio / (10 ** (weight/2));                                                                                                   
   x2=oddsratio * (10 ** (weight/2));
                                                                                                   
   /* Compute top and bottom offsets */                                                                                                    
   if _n_ = nobs then do;                                                                                                                  
      pct=0.75/nobs;                                                                                                                        
      call symputx("pct", pct);                                                                                                             
      call symputx("pct2", 2*pct);                                                                                                          
      call symputx("count", nobs);                                                                                                          
   end;                                                                                                                                    
run;                                                                                                                                    
                                                                                                                                        
ods listing close;                                                                                                                      
ods html image_dpi=100 path="." file='sgplotforest.html';                                                                               
ods graphics / reset width=600px height=400px imagename="Forest_Plot_Vector" imagefmt=gif;                                              
                                                                                                                                        
title "Meta-analysis       ";                                                                                      
title2 h=8pt 'Hedges G and 95% CI';                                                                                                   
                                                                                                                                        
proc sgplot data=forest4 noautolegend;                                                                                                  
   scatter y=study2value x=oddsratio / markerattrs=graphdata2(symbol=diamondfilled size=10);                                            
   scatter y=studyvalue x=oddsratio / xerrorupper=ucl2 xerrorlower=lcl2 markerattrs=graphdata1(symbol=squarefilled size=0);             
   vector x=x2 y=studyvalue / xorigin=x1 yorigin=studyvalue lineattrs=graphdata1(thickness=8) noarrowheads;                             
   scatter y=studyvalue x=or / markerchar=oddsratio x2axis;                                                                             
   scatter y=studyvalue x=lcl / markerchar=lowercl x2axis;                                                                              
   scatter y=studyvalue x=ucl / markerchar=uppercl x2axis;                                                                              
   scatter y=studyvalue x=wt / markerchar=weight x2axis;                                                                                                                                                                     
   refline 0 / axis=x lineattrs=(pattern=shortdash) transparency=0.5;                                                              
   inset '           Favors Sham Treatment'  / position=bottomleft;                                                                             
   inset 'Favors Active Treatment'  / position=bottom;                                                                                           
   xaxis offsetmin=0 offsetmax=0.35 min=-2 max=2 minor display=(nolabel) ;                                                 
   x2axis offsetmin=0.7 display=(noticks nolabel);                                                                                      
   yaxis display=(noticks nolabel) offsetmin=0.1 offsetmax=0.05 values=(1 to &count by 1);                                              
run;                                                                                                                                    
                                                                                                                                        
ods html close;                                                                                                                         
ods listing;

Many thanks for any help!


Accepted Solutions
Solution
‎12-03-2015 05:20 AM
Trusted Advisor
Posts: 1,114

Re: How to fix the weights of this forest plot?

Hello @j4ne,

 

I think that's easy:

   /* Compute marker width */
    c=0.8; /* Factor to adjust absolute marker width */
   x1=oddsratio - c*weight;
   x2=oddsratio + c*weight;

As far as I see, only the relative marker widths have a meaning in the graph. Hence, we can introduce an arbitrary "scale factor" c to adjust the absolute marker width. I started with the "weight/2" from your code, i.e. c=0.5, but this seemed to be too small to distinguish between weights 3% and 4%. After removing "/2", i.e. with c=1, the markers were slightly longer than in your sample output with "correct box size". Therefore, I introduced variable c and set it to 0.8. But you can play around with this factor to obtain "optimal" box sizes.

 

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Solution
‎12-03-2015 05:20 AM
Trusted Advisor
Posts: 1,114

Re: How to fix the weights of this forest plot?

Hello @j4ne,

 

I think that's easy:

   /* Compute marker width */
    c=0.8; /* Factor to adjust absolute marker width */
   x1=oddsratio - c*weight;
   x2=oddsratio + c*weight;

As far as I see, only the relative marker widths have a meaning in the graph. Hence, we can introduce an arbitrary "scale factor" c to adjust the absolute marker width. I started with the "weight/2" from your code, i.e. c=0.5, but this seemed to be too small to distinguish between weights 3% and 4%. After removing "/2", i.e. with c=1, the markers were slightly longer than in your sample output with "correct box size". Therefore, I introduced variable c and set it to 0.8. But you can play around with this factor to obtain "optimal" box sizes.

 

Occasional Contributor
Posts: 7

Re: How to fix the weights of this forest plot?

That's perfect, thank you! You're a lifesaver Smiley Very Happy
☑ This topic is SOLVED.

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