<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Clinical Research | Axel Budde</title><link>https://www.axelbudde.de/tag/clinical-research/</link><atom:link href="https://www.axelbudde.de/tag/clinical-research/index.xml" rel="self" type="application/rss+xml"/><description>Clinical Research</description><generator>Wowchemy (https://wowchemy.com)</generator><language>en-us</language><lastBuildDate>Wed, 01 Jan 2025 00:00:00 +0000</lastBuildDate><image><url>https://www.axelbudde.de/media/logo_hua88faf8356f5e0ce4c7ce3101172801d_103689_300x300_fit_lanczos_3.png</url><title>Clinical Research</title><link>https://www.axelbudde.de/tag/clinical-research/</link></image><item><title>FUN For Fit</title><link>https://www.axelbudde.de/project/fun-for-fit/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0000</pubDate><guid>https://www.axelbudde.de/project/fun-for-fit/</guid><description>&lt;p>&lt;strong>FUN For Fit&lt;/strong> is an R Shiny tool for evaluating the practical significance of item misfit in psychological and educational tests — methods central to Clinical Outcome Assessment (COA) validation.&lt;/p>
&lt;h3 id="features">Features&lt;/h3>
&lt;ul>
&lt;li>Rasch model (1PL) and 2PL IRT analysis of weighted MNSQ fit statistics (TAM package)&lt;/li>
&lt;li>2D IRT modelling to estimate correlation bounds after &lt;a href="https://doi.org/10.1177/0146621617692978" target="_blank" rel="noopener">Köhler &amp;amp; Hartig (2017)&lt;/a>&lt;/li>
&lt;li>Step-guided interface enabling non-technical researchers to conduct psychometric instrument evaluation&lt;/li>
&lt;li>Interactive result visualisation (Plotly)&lt;/li>
&lt;/ul>
&lt;h3 id="relevance">Relevance&lt;/h3>
&lt;p>The methods implemented mirror those used in COA instrument validation in clinical trials — assessing whether individual items of a patient-reported outcome (PRO) measure behave as expected under an IRT model, and quantifying the practical consequences of misfit.&lt;/p></description></item><item><title>SHS World Map</title><link>https://www.axelbudde.de/project/shs-world-map/</link><pubDate>Sun, 01 Jan 2023 00:00:00 +0000</pubDate><guid>https://www.axelbudde.de/project/shs-world-map/</guid><description>&lt;p>&lt;strong>SHS World Map&lt;/strong> is an interactive R Shiny dashboard visualising &lt;a href="https://www.thelancet.com/journals/lancet/article/PIIS0140-6736%2817%2932513-8/fulltext" target="_blank" rel="noopener">Serious Health-Related Suffering (SHS)&lt;/a> burden data across 195 countries, developed for the &lt;strong>Lancet Commission on Palliative Care and Pain Relief&lt;/strong>.&lt;/p>
&lt;p>SHS is a patient-centred epidemiological endpoint operationalising unmet need for palliative care — a direct application of outcome measurement methodology at population scale.&lt;/p>
&lt;h3 id="features">Features&lt;/h3>
&lt;ul>
&lt;li>Interactive choropleth maps with country-level SHS burden estimates&lt;/li>
&lt;li>Time series charts and hierarchical visualisations of health-burden indicators&lt;/li>
&lt;li>Responsive web dashboard with complex filtering for research and advocacy audiences&lt;/li>
&lt;li>Used in regulatory, policy, and clinical research contexts worldwide&lt;/li>
&lt;/ul></description></item></channel></rss>