<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Survival Analysis Actuarial on Actuarial Ninja</title><link>https://www.actuarialninja.com/tags/survival-analysis-actuarial/</link><description>Recent content in Survival Analysis Actuarial on Actuarial Ninja</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sun, 03 Nov 2024 23:14:47 +0000</lastBuildDate><atom:link href="https://www.actuarialninja.com/tags/survival-analysis-actuarial/index.xml" rel="self" type="application/rss+xml"/><item><title>Comparative Analysis of Survival Models: Kaplan-Meier vs Nelson-Aalen for Actuarial Claims Data</title><link>https://www.actuarialninja.com/tutorials/comparative-analysis-of-survival-models-kaplan-meier-vs-nelson-aalen-for-actuarial-claims-data/</link><pubDate>Sun, 03 Nov 2024 23:14:47 +0000</pubDate><guid>https://www.actuarialninja.com/tutorials/comparative-analysis-of-survival-models-kaplan-meier-vs-nelson-aalen-for-actuarial-claims-data/</guid><description>&lt;p&gt;When analyzing actuarial claims data, survival models are indispensable tools for understanding the likelihood of events occurring over time. Two of the most widely used survival models are the Kaplan-Meier estimator and the Nelson-Aalen estimator. Both methods are non-parametric, meaning they don&amp;rsquo;t require the data to follow a specific distribution, making them versatile for a variety of applications, from medical studies to insurance claims analysis. In this article, we&amp;rsquo;ll explore the differences and similarities between these two models, along with practical examples and actionable advice on how to choose the best approach for your data.&lt;/p&gt;</description></item></channel></rss>