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12-02-2015 05:30 AM - edited 12-02-2015 05:33 AM

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):

--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:

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

**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!**

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Solution

12-03-2015
05:20 AM

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Posted in reply to j4ne

12-02-2015 06:32 AM

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

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Posted in reply to j4ne

12-02-2015 06:32 AM

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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Posted in reply to FreelanceReinhard

12-03-2015 05:20 AM

That's perfect, thank you! You're a lifesaver