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Hi everyone, I hope you're all doing well. </div>
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I need your help with something. I'm applying a meta-regression on a dataset where I initially used the
<code>metaprop</code> function to obtain the pooled proportions of hypertension. Now, I'm trying to understand how variables like the year of publication, study type, and publication pathways influence the effect size (proportion) in the meta-analysis. </div>
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Dataset (called "hiper")</div>
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<img size="26199" contenttype="image/png" style="max-width: 1251px;" data-outlook-trace="F:1|T:1" src="cid:7fbab9a8-0f72-44bd-ad97-2e17a7d4568b"></div>
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Here are the scripts I used:</div>
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First, I applied <code>metaprop</code>:</div>
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<img size="25364" contenttype="image/png" style="max-width: 1251px;" data-outlook-trace="F:1|T:1" src="cid:cd051df0-f6ac-4123-ae10-b194bfea08c2"></div>
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Next, I applied the meta-regression:</div>
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<img size="8950" contenttype="image/png" style="max-width: 1251px;" data-outlook-trace="F:1|T:1" src="cid:a0b758aa-ec81-497a-8fd6-208790109d3f"></div>
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After generating the plot (see below), I noticed that without transforming the <code>
TE</code> and <code>seTE</code> values, the proportions on the x-axis appear as negative values. I would like to know if my scripts for the meta-regression are correct and whether it would be necessary to apply a logarithmic transformation (<code>transf.ilogit(m.prop$TE)</code> and
<code>transf.ilogit(m.prop$seTE)</code>) to fix this.</div>
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Additionally, I would appreciate your advice on which method is more appropriate: using the transformed values or the non-transformed ones?</div>
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<img size="92359" contenttype="image/png" style="max-width: 1251px;" data-outlook-trace="F:1|T:1" src="cid:5612e885-24f0-4220-85f4-dc3fcb752570"></div>
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Thanks in advance for your help!</div>
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Best wishes,</div>
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<div style="font-size: 10pt;"><b>Sancho Xavier</b></div>
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Candidate for Postgraduate Programme in Epidemiology in Public Health</div>
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MBA in Data Science and Analytics at USP (ongoing)</div>
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<b>Linkedin:</b> linkedin.com/in/sancho-xavier-59565a18a</div>
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<b>Orcid iD:</b> https://orcid.org/0000-0001-9493-4098</div>
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<b>Web of Science (Clarivate):</b> <a href="https://www.webofscience.com/wos/author/record/GON-5675-2022" id="OWA9f331ddf-d14a-6fbb-6334-01ea640c8589" class="OWAAutoLink">https://www.webofscience.com/wos/author/record/GON-5675-2022</a></div>
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<b>Reference Citation Analysis (RCA): </b><a href="https://referencecitationanalysis.com/00001471" id="OWAe977c27e-e036-af0a-b71f-9d238f9f0da5" class="OWAAutoLink">https://referencecitationanalysis.com/00001471</a></div>
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<b>Whatsapp: </b>+258 852255846 </div>
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