You'll need to see hundreds of past course evaluations to see why, but a main
reason is the learning environment we provide, with hours of discussion among
participants occuring during the 4-day course. This includes topics such as
how to collaborate with non-statisticians especially when explaining the
results of complex statistical models. We also have discussions during the
lunches in the dining hall next to the lecture room. Many of the topics I
cover are set by the participants during the week. And all of the course
handouts are freely available for everyone.
Frank
________________________________
Frank E Harrell Jr Professor School of Medicine
Department of Biostatistics Vanderbilt University
________________________________
From: Graeme Davidson <graeme.r.david...@gmail.com>
Sent: Sunday, March 24, 2019 04:42
To: Harrell, Frank E
Cc: r-help@r-project.org
Subject: Re: [R] Regression Modeling Strategies and the R rms Package Short
Course 2019
Hi Frank,
As part of the R community, you will be aware that the vast majority of
knowledge regarding statistics such as linear modelling is online for free.
What makes this course worthy of payment compared to freely available
information and/or well structured fee paying courses such as DataCamp?
All the best
Graeme R Davidson PhD
Data and Insight Analyst
> On 23 Mar 2019, at 14:41, Harrell, Frank E <f.harr...@vumc.org> wrote:
>
> *Regression Modeling Strategies Short Course 2019*
>
> Frank E. Harrell, Jr., Ph.D., Professor
>
> Department of Biostatistics, Vanderbilt University School of Medicine
>
> fharrell.com @f2harrell
>
>
>
> *May 14-17, 2019* With Optional R Workshop May 13
>
> 9:00am - 4:00pm
>
> Alumni Hall
>
> Vanderbilt University
>
> Nashville Tennessee USA
>
>
>
> See
> https://nam05.safelinks.protection.outlook.com/?url=http%3A%2F%2Fbiostat.mc.vanderbilt.edu%2FRMSShortCourse2019&data=02%7C01%7Cf.harrell%40vumc.org%7C933ae76953c84add589c08d6b03cfa6c%7Cef57503014244ed8b83c12c533d879ab%7C0%7C0%7C636890173287469754&sdata=8GcqD8no7%2FNJ2Ytw%2B0U7DwwKvs6flF2buPvuHc3ra%2Bc%3D&reserved=0
> for details.
>
>
>
> The course includes statistical methodology, case studies, and use of
>
> the R rms package. Emphasis is on developing predictive models, model
> validation, and quantifying predictive accuracy, plus many more topics
> including navigating the choice of statistical models vs. machine learning.
>
>
>
>
>
>
>
> Frank E Harrell Jr Professor School of Medicine
>
> Department of Biostatistics Vanderbilt University
>
>
> ______________________________________________
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://nam05.safelinks.protection.outlook.com/?url=https%3A%2F%2Fstat.ethz.ch%2Fmailman%2Flistinfo%2Fr-help&data=02%7C01%7Cf.harrell%40vumc.org%7C933ae76953c84add589c08d6b03cfa6c%7Cef57503014244ed8b83c12c533d879ab%7C0%7C0%7C636890173287469754&sdata=UTdWE%2BH9AAlL8XytaifKp7BdaLKYwK4zDzb%2B2TaCnRY%3D&reserved=0
> PLEASE do read the posting guide
> https://nam05.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.R-project.org%2Fposting-guide.html&data=02%7C01%7Cf.harrell%40vumc.org%7C933ae76953c84add589c08d6b03cfa6c%7Cef57503014244ed8b83c12c533d879ab%7C0%7C0%7C636890173287469754&sdata=CyHkkgXrAkPTxSh87JUEbvg%2BwmV8LhqZYgYoMWgyzak%3D&reserved=0
> and provide commented, minimal, self-contained, reproducible code.
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