<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Multivariate Analysis on Ahmed Azeez | Portfolio</title><link>https://mscazmy.github.io/tags/multivariate-analysis/</link><description>Recent content in Multivariate Analysis on Ahmed Azeez | Portfolio</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sun, 12 Jul 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://mscazmy.github.io/tags/multivariate-analysis/index.xml" rel="self" type="application/rss+xml"/><item><title>Reporting Standards for Exploratory Factor Analysis: A Guide to Transparency</title><link>https://mscazmy.github.io/2026/07/12/efa-reporting-standards/</link><pubDate>Sun, 12 Jul 2026 00:00:00 +0000</pubDate><guid>https://mscazmy.github.io/2026/07/12/efa-reporting-standards/</guid><description>Exploratory Factor Analysis (EFA) is a multivariate statistical method used to determine the underlying dimensions, factors, or latent variables within a set of observed variables. To ensure your findings are replicable and interpretable, specific technical details must be transparently reported.
The Foundation: Justification &amp;amp; DataBefore diving into the numbers, researchers must justify the use of EFA over other methods like Confirmatory Factor Analysis (CFA). This is typically necessary when the factor structure is previously unknown or when developing a new scale.</description></item></channel></rss>