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<p>Thank you very much for the quick Reply and your advice!</p>
<p><br>
</p>
<p>That Explanation makes a lot of sense.</p>
<p>I have now tried using pairwise() to calculate the SMDs:</p>
<p><br>
</p>
<p></p>
<div><span style="font-family:"Lucida Console",Monaco,monospace; font-size:8pt">paired<- pairwise(list(TR1, TR2),</span><br>
<span style="font-family:"Lucida Console",Monaco,monospace; font-size:8pt"> n = list(n_TR1, n_TR2),</span><br>
<span style="font-family:"Lucida Console",Monaco,monospace; font-size:8pt"> mean = list(Mt2TR1, Mt2TR2),</span><br>
<span style="font-family:"Lucida Console",Monaco,monospace; font-size:8pt"> sd = list(SDt2TR1, SDt2TR2),</span><br>
<span style="font-family:"Lucida Console",Monaco,monospace; font-size:8pt"> data = DATA1, studlab = studlab, sm= "SMD")</span><br>
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<p><br>
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<p>This is an exerpt from the data Frame; </p>
<p>3-arm study in <span style="color:rgb(189,19,152)">Purple<span style="color:rgb(0,0,0)">:</span></span></p>
<p><br>
</p>
<p></p>
<div> <span style="font-family:"Lucida Console",Monaco,monospace; font-size:8pt">
<span style="font-family:"Lucida Console",Monaco,monospace; font-size:8pt">studlab treat1 treat2 n1 mean1 sd1 n2 mean2 sd2 TE seTE age females severity income</span></span><br>
<span style="font-family:"Lucida Console",Monaco,monospace; font-size:8pt">1 1 EMDR WL 15 22.87 20.27 14 54.21 16.26 -1.65116388 0.4387386 36.54 0.76 clinical lowmid</span><br>
<span style="font-family:"Lucida Console",Monaco,monospace; font-size:8pt">44 100 NET WL 19 55.07 27.01 19 76.86 17.14 -0.94310177 0.3439769 29.40 0.31 clinical high income</span><br>
<span style="font-family:"Lucida Console",Monaco,monospace; font-size:8pt">45 104 NET PsEd 17 19.10 11.70 12 21.20 9.40 -0.18860625 0.3779770 32.85 0.62 clinical lowmid</span><br>
<span style="color:rgb(189,19,152); font-family:"Lucida Console",Monaco,monospace; font-size:8pt">48 107 MBI PsEd 68 46.90 18.20 66 55.20 15.30 -0.49022797 0.1754460 47.04 0.17 clinical high income</span><br>
<span style="color:rgb(189,19,152); font-family:"Lucida Console",Monaco,monospace; font-size:8pt">47 107 PE PsEd 68 50.60 18.50 66 55.20 15.30 -0.26905282 0.1735963 47.04 0.17 clinical high income</span><br>
<span style="color:rgb(189,19,152); font-family:"Lucida Console",Monaco,monospace; font-size:8pt">46 107 PE MBI 68 50.60 18.50 68 46.90 18.20 0.20049752 0.1719418 47.04 0.17 clinical high income</span><br>
<span style="font-family:"Lucida Console",Monaco,monospace; font-size:8pt">78 11 MBI WL NA NA NA NA NA NA -0.48920000 0.2800000 51.80 0.99 <NA> high income</span></div>
<div><span style="font-family:"Lucida Console",Monaco,monospace; font-size:8pt"><br>
</span></div>
<div><span style="font-family:"Lucida Console",Monaco,monospace; font-size:8pt">
<div><span style="font-family:"Lucida Console",Monaco,monospace; font-size:8pt"> </span><span style="font-family:"Lucida Console",Monaco,monospace; font-size:8pt"> sample arms self_exp n_total tr_size analysis</span><br>
<span style="font-family:"Lucida Console",Monaco,monospace; font-size:8pt"> </span><br>
<span style="font-family:"Lucida Console",Monaco,monospace; font-size:8pt">1 refugees 2 self-rated 29 very small completers</span><br>
<span style="font-family:"Lucida Console",Monaco,monospace; font-size:8pt">44 refugees 2 clinician-rated 38 very small ITT</span><br>
<span style="font-family:"Lucida Console",Monaco,monospace; font-size:8pt">45 refugees 2 self-rated 29 very small ITT</span><br>
<span style="color:rgb(189,19,152); font-family:"Lucida Console",Monaco,monospace; font-size:8pt">48 vetmil 3 self-rated 134 large ITT</span><br>
<span style="color:rgb(189,19,152); font-family:"Lucida Console",Monaco,monospace; font-size:8pt">47 vetmil 3 self-rated 134 large ITT</span><br>
<span style="color:rgb(189,19,152); font-family:"Lucida Console",Monaco,monospace; font-size:8pt">46 vetmil 3 self-rated 136 large ITT</span><br>
<span style="font-family:"Lucida Console",Monaco,monospace; font-size:8pt">78 civilian 2 self-rated 71 small-moderate ITT</span></div>
<br>
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<br>
<p></p>
<p><span style="display:inline!important; float:none; background-color:rgb(255,255,255); color:rgb(0,0,0); font-family:Calibri,Helvetica,sans-serif,"EmojiFont","Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols; font-size:16px; font-style:normal; font-variant:normal; font-weight:400; letter-spacing:normal; orphans:2; text-align:left; text-decoration:none; text-indent:0px; text-transform:none; white-space:normal; word-spacing:0px">However,
I still get the same </span><span style="display:inline!important; float:none; background-color:rgb(255,255,255); color:rgb(0,0,0); font-family:Calibri,Helvetica,sans-serif,"EmojiFont","Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols; font-size:16px; font-style:normal; font-variant:normal; font-weight:400; letter-spacing:normal; orphans:2; text-align:left; text-decoration:none; text-indent:0px; text-transform:none; white-space:normal; word-spacing:0px">error
message</span><span style="display:inline!important; float:none; background-color:rgb(255,255,255); color:rgb(0,0,0); font-family:Calibri,Helvetica,sans-serif,"EmojiFont","Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols; font-size:16px; font-style:normal; font-variant:normal; font-weight:400; letter-spacing:normal; orphans:2; text-align:left; text-decoration:none; text-indent:0px; text-transform:none; white-space:normal; word-spacing:0px">
in the Network meta-Analysis.</span><br>
</p>
<p>A more detailed copy of the Output is available if needed.</p>
<p><br>
</p>
<p>Any advice is very much appreciated!</p>
<p>Best regards,</p>
<p>Rebecca</p>
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<div id="x_divRplyFwdMsg" dir="ltr"><font face="Calibri, sans-serif" color="#000000" style="font-size:11pt"><b>Von:</b> Guido Schwarzer <sc@imbi.uni-freiburg.de><br>
<b>Gesendet:</b> Freitag, 7. Februar 2020 17:49:50<br>
<b>An:</b> Rogasch, Rebecca Manuela Madeleine; r-sig-meta-analysis@r-project.org<br>
<b>Betreff:</b> Re: [R-meta] [netmeta] Error message in network meta-analysis: "Problem with multi-arm studies: Studies with inconsistent treatment estimates"</font>
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<font size="2"><span style="font-size:10pt;">
<div class="PlainText">Hi Rebecca,<br>
<br>
I assume the problem is related to calculating SMDs in multi-arm <br>
studies. Each pairwise comparison (in a multi-arm study) uses a <br>
different pooled standard deviation to calculate the SMD which leads to <br>
inconsistent effects.<br>
<br>
You could / should use pairwise() to calculate the SMDs which considers <br>
the same pooled standard deviation to calculate the SMD in multi-arm <br>
studies.<br>
<br>
Best wishes, Guido<br>
<br>
-- <br>
Dr. Guido Schwarzer<br>
Institute of Medical Biometry and Statistics,<br>
Faculty of Medicine and Medical Center - University of Freiburg<br>
<br>
Postal address: Stefan-Meier-Str. 26, D-79104 Freiburg<br>
<br>
Phone: +49/761/203-6668<br>
Mail: sc@imbi.uni-freiburg.de<br>
Homepage: <a href="http://www.imbi.uni-freiburg.de">http://www.imbi.uni-freiburg.de</a><br>
<br>
ORCID iD: <a href="https://orcid.org/0000-0001-6214-9087">https://orcid.org/0000-0001-6214-9087</a><br>
R-book: <a href="https://www.springer.com/gp/book/9783319214153">https://www.springer.com/gp/book/9783319214153</a><br>
<br>
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