<?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>rafhq1403.r-universe.dev</title><link>https://rafhq1403.r-universe.dev</link><description>Recent package updates in rafhq1403</description><generator>R-universe</generator><image><url>https://github.com/rafhq1403.png</url><title>R packages by rafhq1403</title><link>https://rafhq1403.r-universe.dev</link></image><lastBuildDate>Wed, 03 Jun 2026 21:03:59 GMT</lastBuildDate><item><title>[rafhq1403] contentValidity 0.2.0</title><author>rashed.alqahtani@gmail.com (Rashed Alqahtani)</author><description>Computes content validity indices commonly used in
instrument development and questionnaire validation, including
the Item-level Content Validity Index (I-CVI), Scale-level
Content Validity Index (S-CVI), modified kappa adjusted for
chance agreement, Aiken's V, and Lawshe's Content Validity
Ratio (CVR). Methods follow Lynn (1986)
&lt;doi:10.1097/00006199-198611000-00017&gt;, Polit and Beck (2006)
&lt;doi:10.1002/nur.20147&gt;, Aiken (1985)
&lt;doi:10.1177/0013164485451012&gt;, and Lawshe (1975)
&lt;doi:10.1111/j.1744-6570.1975.tb01393.x&gt;.</description><link>https://github.com/r-universe/rafhq1403/actions/runs/28650647572</link><pubDate>Wed, 03 Jun 2026 21:03:59 GMT</pubDate><r:package>contentValidity</r:package><r:version>0.2.0</r:version><r:status>success</r:status><r:repository>https://rafhq1403.r-universe.dev</r:repository><r:upstream>https://github.com/rafhq1403/contentvalidity</r:upstream><r:article><r:source>getting-started.Rmd</r:source><r:filename>getting-started.html</r:filename><r:title>Getting Started with contentValidity</r:title><r:created>2026-05-05 19:32:54</r:created><r:modified>2026-06-03 20:42:50</r:modified></r:article></item><item><title>[rafhq1403] mcqAnalysis 0.1.0</title><author>rashed.alqahtani@gmail.com (Rashed Alqahtani)</author><description>A unified toolkit for classical test theory (CTT) item
analysis of multiple-choice test data, including item
difficulty (p-value), item discrimination (point-biserial
correlation and upper-lower 27-percent discrimination index),
per-distractor analysis (frequency, proportion, and
discrimination), and Haladyna's distractor efficiency. A
wrapper function returns a tidy 'mcq_analysis' object with
print, plot (difficulty-discrimination scatter), and APA-style
table methods for direct inclusion in journal manuscripts.
Implemented in pure R with no compiled code and minimal
dependencies.</description><link>https://github.com/r-universe/rafhq1403/actions/runs/27534241395</link><pubDate>Tue, 12 May 2026 07:21:32 GMT</pubDate><r:package>mcqAnalysis</r:package><r:version>0.1.0</r:version><r:status>success</r:status><r:repository>https://rafhq1403.r-universe.dev</r:repository><r:upstream>https://github.com/rafhq1403/mcqanalysis</r:upstream><r:article><r:source>getting-started.Rmd</r:source><r:filename>getting-started.html</r:filename><r:title>Getting started with mcqAnalysis</r:title><r:created>2026-05-12 06:41:18</r:created><r:modified>2026-05-12 07:19:58</r:modified></r:article></item></channel></rss>