<?xml version="1.0" encoding="utf-8" ?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:r="https://r-universe.dev"><channel><title>dom-muston.r-universe.dev</title><link>https://dom-muston.r-universe.dev</link><description>Recent package updates in dom-muston</description><generator>R-universe</generator><image><url>https://github.com/dom-muston.png</url><title>R packages by dom-muston</title><link>https://dom-muston.r-universe.dev</link></image><lastBuildDate>Fri, 10 Jul 2026 17:49:18 GMT</lastBuildDate><item><title>[merck] psm3mkv 0.3.3</title><author>dom.muston@gmail.com (Dominic Muston)</author><description>Fits and evaluates three-state partitioned survival
analyses (PartSAs) and Markov models (clock forward or clock
reset) to progression and overall survival data typically
collected in oncology clinical trials. These model structures
are typically considered in cost-effectiveness modeling in
advanced/metastatic cancer indications. Muston (2024).
&quot;Informing structural assumptions for three state oncology
cost-effectiveness models through model efficiency and fit&quot;.
Applied Health Economics and Health Policy.</description><link>https://github.com/r-universe/merck/actions/runs/37763793788</link><pubDate>Fri, 10 Jul 2026 17:49:18 GMT</pubDate><r:package>psm3mkv</r:package><r:version>0.3.3</r:version><r:status>success</r:status><r:repository>https://merck.r-universe.dev</r:repository><r:upstream>https://github.com/merck/psm3mkv</r:upstream><r:article><r:source>example.Rmd</r:source><r:filename>example.html</r:filename><r:title>Example use of psm3mkv</r:title><r:created>2023-09-01 16:15:54</r:created><r:modified>2024-06-07 19:35:11</r:modified></r:article><r:article><r:source>mortality-adjustments.Rmd</r:source><r:filename>mortality-adjustments.html</r:filename><r:title>Mortality adjustments</r:title><r:created>2024-04-08 02:58:36</r:created><r:modified>2024-06-07 19:35:11</r:modified></r:article></item><item><title>[msdllcpapers] dynamicpv 0.4.2</title><author>dom.muston@gmail.com (Dominic Muston)</author><description>The goal of 'dynamicpv' is to provide a simple way to
calculate (net) present values and outputs from health economic
models (especially cost-effectiveness and budget impact) in
discrete time that reflect dynamic pricing and dynamic uptake.
Dynamic pricing is also known as life cycle pricing; dynamic
uptake is also known as multiple or stacked cohorts, or dynamic
disease prevalence. Shafrin (2024) &lt;doi:10.1515/fhep-2024-0014&gt;
provides an explanation of dynamic value elements, in the
context of Generalized Cost Effectiveness Analysis, and Puls
(2024) &lt;doi:10.1016/j.jval.2024.03.006&gt; reviews challenges of
incorporating such dynamic value elements. This package aims to
reduce those challenges.</description><link>https://github.com/r-universe/msdllcpapers/actions/runs/37776449891</link><pubDate>Wed, 29 Apr 2026 21:55:37 GMT</pubDate><r:package>dynamicpv</r:package><r:version>0.4.2</r:version><r:status>success</r:status><r:repository>https://msdllcpapers.r-universe.dev</r:repository><r:upstream>https://github.com/msdllcpapers/dynamicpv</r:upstream><r:article><r:source>budget-impact-applications.Rmd</r:source><r:filename>budget-impact-applications.html</r:filename><r:title>Budget Impact Applications</r:title><r:created>2025-10-07 16:53:16</r:created><r:modified>2026-03-11 21:28:27</r:modified></r:article><r:article><r:source>cost-effectiveness-applications.Rmd</r:source><r:filename>cost-effectiveness-applications.html</r:filename><r:title>Cost-Effectiveness Applications</r:title><r:created>2025-09-28 18:00:43</r:created><r:modified>2026-01-10 22:20:06</r:modified></r:article><r:article><r:source>math-framework.Rmd</r:source><r:filename>math-framework.html</r:filename><r:title>Mathematical Framework</r:title><r:created>2026-01-10 22:20:06</r:created><r:modified>2026-01-10 22:20:06</r:modified></r:article><r:article><r:source>net-present-value.Rmd</r:source><r:filename>net-present-value.html</r:filename><r:title>Net Present Value</r:title><r:created>2026-01-10 22:20:06</r:created><r:modified>2026-01-10 22:20:06</r:modified></r:article></item></channel></rss>